=============================================================================== About this build: this rebuild has been done as part of reproduce.debian.net where we aim to reproduce Debian binary packages distributed via ftp.debian.org, by rebuilding using the exact same packages as the original build on the buildds, as described in the relevant .buildinfo file from buildinfos.debian.net. For more information please go to https://reproduce.debian.net or join #debian-reproducible on irc.debian.org =============================================================================== Preparing download of sources for /srv/rebuilderd/tmp/rebuilderdrdSFyz/inputs/statsmodels_0.14.5+dfsg-1_all.buildinfo Source: statsmodels Version: 0.14.5+dfsg-1 rebuilderd-worker node: ionos23-amd64 +------------------------------------------------------------------------------+ | Downloading sources Thu, 02 Oct 2025 08:32:28 +0000 | +------------------------------------------------------------------------------+ Get:1 https://deb.debian.org/debian trixie InRelease [140 kB] Get:2 https://deb.debian.org/debian-security trixie-security InRelease [43.4 kB] Get:3 https://deb.debian.org/debian trixie-updates InRelease [47.3 kB] Get:4 https://deb.debian.org/debian trixie-proposed-updates InRelease [55.8 kB] Get:5 https://deb.debian.org/debian trixie-backports InRelease [53.8 kB] Get:6 https://deb.debian.org/debian forky InRelease [147 kB] Get:7 https://deb.debian.org/debian sid InRelease [207 kB] Get:8 https://deb.debian.org/debian experimental InRelease [101 kB] Get:9 https://deb.debian.org/debian trixie/main Sources [10.5 MB] Get:10 https://deb.debian.org/debian trixie/non-free-firmware Sources [6536 B] Get:11 https://deb.debian.org/debian-security trixie-security/main Sources [54.7 kB] Get:12 https://deb.debian.org/debian trixie-updates/main Sources [2788 B] Get:13 https://deb.debian.org/debian trixie-proposed-updates/main Sources [22.3 kB] Get:14 https://deb.debian.org/debian trixie-backports/non-free-firmware Sources [1052 B] Get:15 https://deb.debian.org/debian trixie-backports/main Sources [51.6 kB] Get:16 https://deb.debian.org/debian forky/main Sources [10.7 MB] Get:17 https://deb.debian.org/debian forky/non-free-firmware Sources [7128 B] Get:18 https://deb.debian.org/debian sid/non-free-firmware Sources [9100 B] Get:19 https://deb.debian.org/debian sid/main Sources [11.1 MB] Get:20 https://deb.debian.org/debian experimental/main Sources [374 kB] Get:21 https://deb.debian.org/debian experimental/non-free-firmware Sources [2572 B] Fetched 33.7 MB in 3s (10.5 MB/s) Reading package lists... 'https://deb.debian.org/debian/pool/main/s/statsmodels/statsmodels_0.14.5%2bdfsg-1.dsc' statsmodels_0.14.5+dfsg-1.dsc 3873 SHA256:c0960046ba86ebb6ee1459b9792eecedd7a680b4be166578801184cc146ee6a0 'https://deb.debian.org/debian/pool/main/s/statsmodels/statsmodels_0.14.5%2bdfsg.orig.tar.xz' statsmodels_0.14.5+dfsg.orig.tar.xz 12137092 SHA256:45e1017295e4bd2ef4d280bdc40ff076f977deb77fc1eb73a3ca01ea127c952c 'https://deb.debian.org/debian/pool/main/s/statsmodels/statsmodels_0.14.5%2bdfsg-1.debian.tar.xz' statsmodels_0.14.5+dfsg-1.debian.tar.xz 36656 SHA256:7d7bf8809629801e4da718b2795fb5a3b69125bcae7d2f709ef1f851fb1247c3 45e1017295e4bd2ef4d280bdc40ff076f977deb77fc1eb73a3ca01ea127c952c statsmodels_0.14.5+dfsg.orig.tar.xz 7d7bf8809629801e4da718b2795fb5a3b69125bcae7d2f709ef1f851fb1247c3 statsmodels_0.14.5+dfsg-1.debian.tar.xz c0960046ba86ebb6ee1459b9792eecedd7a680b4be166578801184cc146ee6a0 statsmodels_0.14.5+dfsg-1.dsc +------------------------------------------------------------------------------+ | Calling debrebuild Thu, 02 Oct 2025 08:32:32 +0000 | +------------------------------------------------------------------------------+ Rebuilding statsmodels=0.14.5+dfsg-1 in /srv/rebuilderd/tmp/rebuilderdrdSFyz/inputs now. + nice /usr/bin/debrebuild --buildresult=/srv/rebuilderd/tmp/rebuilderdrdSFyz/out --builder=sbuild+unshare --cache=/srv/rebuilderd/cache -- /srv/rebuilderd/tmp/rebuilderdrdSFyz/inputs/statsmodels_0.14.5+dfsg-1_all.buildinfo /srv/rebuilderd/tmp/rebuilderdrdSFyz/inputs/statsmodels_0.14.5+dfsg-1_all.buildinfo contains a GPG signature which has NOT been validated Using defined Build-Path: /build/reproducible-path/statsmodels-0.14.5+dfsg I: verifying dsc... successful! Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid InRelease [216 kB] Get:2 http://snapshot.debian.org/archive/debian/20250904T023413Z sid InRelease [216 kB] Get:3 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 Packages [10.2 MB] Get:4 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 Packages [10.2 MB] Fetched 20.8 MB in 2s (10.5 MB/s) Reading package lists... W: http://snapshot.debian.org/archive/debian/20250828T083238Z/dists/sid/InRelease: Loading /etc/apt/trusted.gpg from deprecated option Dir::Etc::Trusted W: http://snapshot.debian.org/archive/debian/20250904T023413Z/dists/sid/InRelease: Loading /etc/apt/trusted.gpg from deprecated option Dir::Etc::Trusted Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-requirejs-text all 2.0.12-1.1 [9016 B] Fetched 9016 B in 0s (897 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp58j145mo/libjs-requirejs-text_2.0.12-1.1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libcurl3t64-gnutls amd64 8.16.0~rc2-1 [391 kB] Fetched 391 kB in 0s (35.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp5bqh16lj/libcurl3t64-gnutls_8.16.0~rc2-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libk5crypto3 amd64 1.21.3-5 [81.5 kB] Fetched 81.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpokia2l4s/libk5crypto3_1.21.3-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-referencing all 0.36.2-1 [23.7 kB] Fetched 23.7 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpzahiwxed/python3-referencing_0.36.2-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-rpy2 amd64 3.5.17-2 [213 kB] Fetched 213 kB in 0s (436 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpyi9czanv/python3-rpy2_3.5.17-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 fontconfig-config amd64 2.15.0-2.3 [318 kB] Fetched 318 kB in 0s (29.9 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpau8gpd0u/fontconfig-config_2.15.0-2.3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-zmq amd64 26.4.0-1 [178 kB] Fetched 178 kB in 0s (14.9 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpvj56wd37/python3-zmq_26.4.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-nbsphinx all 0.9.5+ds-1 [39.9 kB] Fetched 39.9 kB in 0s (3821 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpq6gzqrbx/python3-nbsphinx_0.9.5+ds-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 dwz amd64 0.15-1+b1 [110 kB] Fetched 110 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpycuaer3a/dwz_0.15-1+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libfile-stripnondeterminism-perl all 1.14.2-1 [19.8 kB] Fetched 19.8 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpjdhh__ls/libfile-stripnondeterminism-perl_1.14.2-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libsodium23 amd64 1.0.18-1+b2 [165 kB] Fetched 165 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpyk38hom6/libsodium23_1.0.18-1+b2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libudev1 amd64 258~rc3-1 [156 kB] Fetched 156 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp1w907ps0/libudev1_258~rc3-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-littler amd64 0.3.21-1 [107 kB] Fetched 107 kB in 0s (849 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpuj85_f2p/r-cran-littler_0.3.21-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libsvtav1enc2 amd64 2.3.0+dfsg-1 [2489 kB] Fetched 2489 kB in 0s (116 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp2qxhmtfk/libsvtav1enc2_2.3.0+dfsg-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 binutils-common amd64 2.45-4 [2556 kB] Fetched 2556 kB in 0s (124 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpbg7rvyp3/binutils-common_2.45-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpipeline1 amd64 1.5.8-1 [42.0 kB] Fetched 42.0 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpx18uvgrw/libpipeline1_1.5.8-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-send2trash all 1.8.3-1 [15.8 kB] Fetched 15.8 kB in 0s (134 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpzdzg_c8s/python3-send2trash_1.8.3-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libtool all 2.5.4-4 [539 kB] Fetched 539 kB in 0s (48.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpuwr616x6/libtool_2.5.4-4_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-nest-asyncio all 1.5.4-1 [6248 B] Fetched 6248 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp66nql43m/python3-nest-asyncio_1.5.4-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-reformulas all 0.4.1-1 [127 kB] Fetched 127 kB in 0s (816 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp1kzcn474/r-cran-reformulas_0.4.1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-sp amd64 1:2.2-0+dfsg-1 [1445 kB] Fetched 1445 kB in 0s (5078 kB/s) dpkg-name: info: moved 'r-cran-sp_1%3a2.2-0+dfsg-1_amd64.deb' to '/srv/rebuilderd/tmp/tmp0wec9i8a/r-cran-sp_2.2-0+dfsg-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libipt2 amd64 2.1.2-1 [47.8 kB] Fetched 47.8 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpihzo4e5d/libipt2_2.1.2-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 g++-14-x86-64-linux-gnu amd64 14.3.0-5 [12.1 MB] Fetched 12.1 MB in 0s (100 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmplv3i3coq/g++-14-x86-64-linux-gnu_14.3.0-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-tornado amd64 6.4.2-3 [349 kB] Fetched 349 kB in 0s (30.5 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmps6t3ios6/python3-tornado_6.4.2-3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libnuma1 amd64 2.0.19-1 [22.2 kB] Fetched 22.2 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmphj4w_f9s/libnuma1_2.0.19-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-colorspace amd64 2.1-1+dfsg-1 [1716 kB] Fetched 1716 kB in 0s (98.1 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp787w1t77/r-cran-colorspace_2.1-1+dfsg-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-babel all 2.17.0-1 [117 kB] Fetched 117 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp3o5qtph5/python3-babel_2.17.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-typing-extensions all 4.15.0-1 [92.4 kB] Fetched 92.4 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpaj6m3sg8/python3-typing-extensions_4.15.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-rcppeigen amd64 0.3.4.0.2-1 [1411 kB] Fetched 1411 kB in 0s (91.5 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpcijrdip6/r-cran-rcppeigen_0.3.4.0.2-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 dh-python all 6.20250414 [116 kB] Fetched 116 kB in 0s (11.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpozs05hos/dh-python_6.20250414_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3 amd64 3.13.7-1 [28.3 kB] Fetched 28.3 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmprmtrje2u/python3_3.13.7-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-jaraco.text all 4.0.0-1 [11.4 kB] Fetched 11.4 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpvsslviw2/python3-jaraco.text_4.0.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-jupyter-client all 8.6.3-2 [92.4 kB] Fetched 92.4 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpua7xcdbw/python3-jupyter-client_8.6.3-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-jsonschema all 4.19.2-6 [71.4 kB] Fetched 71.4 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpqiefitzb/python3-jsonschema_4.19.2-6_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjson-perl all 4.10000-1 [87.5 kB] Fetched 87.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp76rzrfnk/libjson-perl_4.10000-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-nbformat all 5.9.1-1 [45.1 kB] Fetched 45.1 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpsx0b0xcg/python3-nbformat_5.9.1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-doc all 3.13.7-1 [10.4 kB] Fetched 10.4 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp8enqbhzu/python3-doc_3.13.7-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpaper2 amd64 2.2.5-0.3+b2 [16.7 kB] Fetched 16.7 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp93ckz1s_/libpaper2_2.2.5-0.3+b2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 sensible-utils all 0.0.26 [27.0 kB] Fetched 27.0 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp3w1_swg3/sensible-utils_0.0.26_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpixman-1-0 amd64 0.44.0-3 [248 kB] Fetched 248 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpvtqixggq/libpixman-1-0_0.44.0-3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-executing all 2.2.0-0.3 [24.6 kB] Fetched 24.6 kB in 0s (2437 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpse6lpyla/python3-executing_2.2.0-0.3_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 g++ amd64 4:14.2.0-1 [1344 B] Fetched 1344 B in 0s (0 B/s) dpkg-name: info: moved 'g++_4%3a14.2.0-1_amd64.deb' to '/srv/rebuilderd/tmp/tmpx_fw4bms/g++_14.2.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 unicode-data all 15.1.0-1 [8547 kB] Fetched 8547 kB in 0s (170 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpdsk8z6h4/unicode-data_15.1.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libsframe2 amd64 2.45-4 [79.5 kB] Fetched 79.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp79k7dy_h/libsframe2_2.45-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-nlme amd64 3.1.168-1 [2329 kB] Fetched 2329 kB in 0s (116 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpdn8hgw79/r-cran-nlme_3.1.168-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-zipp all 3.21.0-1 [10.6 kB] Fetched 10.6 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp53pzy_2i/python3-zipp_3.21.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libkrb5-3 amd64 1.21.3-5 [326 kB] Fetched 326 kB in 0s (32.1 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpqkll_y47/libkrb5-3_1.21.3-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 perl-base amd64 5.40.1-6 [1666 kB] Fetched 1666 kB in 0s (92.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpz85jakmg/perl-base_5.40.1-6_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libgraphite2-3 amd64 1.3.14-3 [75.1 kB] Fetched 75.1 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpqztqa948/libgraphite2-3_1.3.14-3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-deoptimr all 1.1-4-1 [76.8 kB] Fetched 76.8 kB in 0s (348 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp908i0__9/r-cran-deoptimr_1.1-4-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 coreutils amd64 9.7-3 [3024 kB] Fetched 3024 kB in 0s (121 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpbg6z2z2t/coreutils_9.7-3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-robustbase amd64 0.99-4-1-1 [3050 kB] Fetched 3050 kB in 0s (9647 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpgey2qn_x/r-cran-robustbase_0.99-4-1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-idna all 3.10-1 [42.0 kB] Fetched 42.0 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpkwoh_8c6/python3-idna_3.10-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-minqa amd64 1.2.8-1 [118 kB] Fetched 118 kB in 0s (874 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp8piqcntq/r-cran-minqa_1.2.8-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-setuptools-scm all 8.2.1-2 [41.3 kB] Fetched 41.3 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpn2dkz3s3/python3-setuptools-scm_8.2.1-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-generics all 0.1.3-1 [81.4 kB] Fetched 81.4 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpbgz58jzv/r-cran-generics_0.1.3-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libcurl4t64 amd64 8.16.0~rc2-1 [398 kB] Fetched 398 kB in 0s (33.4 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpsew02ci9/libcurl4t64_8.16.0~rc2-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-codemirror all 5.65.20+~cs5.83.25-1 [733 kB] Fetched 733 kB in 0s (60.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpwl7ftu7y/libjs-codemirror_5.65.20+~cs5.83.25-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-pandas all 2.2.3+dfsg-9 [3097 kB] Fetched 3097 kB in 0s (131 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp_qfiaowi/python3-pandas_2.2.3+dfsg-9_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libidn2-0 amd64 2.3.8-4 [110 kB] Fetched 110 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmplqh0ydg2/libidn2-0_2.3.8-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 liblerc4 amd64 4.0.0+ds-5 [183 kB] Fetched 183 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp1q1vez9o/liblerc4_4.0.0+ds-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpgm-5.3-0t64 amd64 5.3.128~dfsg-2.1+b1 [162 kB] Fetched 162 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpljhvgzei/libpgm-5.3-0t64_5.3.128~dfsg-2.1+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-stack-data all 0.6.3-1 [21.6 kB] Fetched 21.6 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp_trz6xlw/python3-stack-data_0.6.3-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libc6-dev amd64 2.41-12 [1991 kB] Fetched 1991 kB in 0s (112 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpolu9a8mg/libc6-dev_2.41-12_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-jinja2 all 3.1.6-1 [107 kB] Fetched 107 kB in 0s (1074 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpawlhly7b/python3-jinja2_3.1.6-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3.13-dev amd64 3.13.7-1 [504 kB] Fetched 504 kB in 0s (7406 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpyoulhij5/python3.13-dev_3.13.7-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libgcc-14-dev amd64 14.3.0-5 [2671 kB] Fetched 2671 kB in 0s (58.9 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpwme0h1lm/libgcc-14-dev_14.3.0-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libxrender1 amd64 1:0.9.12-1 [27.9 kB] Fetched 27.9 kB in 0s (128 kB/s) dpkg-name: info: moved 'libxrender1_1%3a0.9.12-1_amd64.deb' to '/srv/rebuilderd/tmp/tmpka_87mhn/libxrender1_0.9.12-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 file amd64 1:5.46-5 [43.6 kB] Fetched 43.6 kB in 0s (206 kB/s) dpkg-name: info: moved 'file_1%3a5.46-5_amd64.deb' to '/srv/rebuilderd/tmp/tmpkn4qvhbk/file_5.46-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libnghttp2-14 amd64 1.64.0-1.1+b1 [76.2 kB] Fetched 76.2 kB in 0s (403 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmplihgpc_z/libnghttp2-14_1.64.0-1.1+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-fs all 2.4.16-7 [95.2 kB] Fetched 95.2 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpe10rr3e0/python3-fs_2.4.16-7_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-mistune all 3.1.3-1 [35.5 kB] Fetched 35.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpl0a0ky26/python3-mistune_3.1.3-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-es6-promise all 4.2.8-12 [15.9 kB] Fetched 15.9 kB in 0s (135 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp5b54bm0a/libjs-es6-promise_4.2.8-12_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-traitlets all 5.14.3+really5.14.3-1 [70.9 kB] Fetched 70.9 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp8ebc6nzz/python3-traitlets_5.14.3+really5.14.3-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 r-cran-matrix amd64 1.7-4-1 [4144 kB] Fetched 4144 kB in 1s (5163 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmporarc_k2/r-cran-matrix_1.7-4-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libgprofng0 amd64 2.45-4 [810 kB] Fetched 810 kB in 0s (64.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp8tmugukf/libgprofng0_2.45-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-sphinx all 8.2.3-2 [477 kB] Fetched 477 kB in 0s (42.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp5qzatpe7/python3-sphinx_8.2.3-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libwebpmux3 amd64 1.5.0-0.1 [126 kB] Fetched 126 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmplvc6afu8/libwebpmux3_1.5.0-0.1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-certifi all 2025.1.31+ds-1 [9652 B] Fetched 9652 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp7kyza4ap/python3-certifi_2025.1.31+ds-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 media-types all 13.0.0 [29.3 kB] Fetched 29.3 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp4ptokssq/media-types_13.0.0_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpython3.13-dev amd64 3.13.7-1 [5279 kB] Fetched 5279 kB in 0s (145 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp7qzz_07n/libpython3.13-dev_3.13.7-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 tar amd64 1.35+dfsg-3.1 [815 kB] Fetched 815 kB in 0s (62.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpcvmlucpo/tar_1.35+dfsg-3.1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-dplyr amd64 1.1.4-4 [1543 kB] Fetched 1543 kB in 0s (49.5 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpdc9fyyn_/r-cran-dplyr_1.1.4-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 readline-common all 8.3-2 [74.8 kB] Fetched 74.8 kB in 0s (783 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpn_f_fute/readline-common_8.3-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 xdg-utils all 1.2.1-2 [75.8 kB] Fetched 75.8 kB in 0s (341 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpks7e4mjs/xdg-utils_1.2.1-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libdpkg-perl all 1.22.21 [650 kB] Fetched 650 kB in 0s (2654 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp5vzua4pd/libdpkg-perl_1.22.21_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libbinutils amd64 2.45-4 [539 kB] Fetched 539 kB in 0s (3288 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpv7xb4oez/libbinutils_2.45-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libcom-err2 amd64 1.47.2-3+b3 [25.0 kB] Fetched 25.0 kB in 0s (53.2 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpfdl2wqaf/libcom-err2_1.47.2-3+b3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-yapf all 0.43.0-1 [178 kB] Fetched 178 kB in 0s (358 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmphkungqpk/python3-yapf_0.43.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 cython3 amd64 3.0.11+dfsg-2+b1 [2504 kB] Fetched 2504 kB in 0s (121 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp2rw0cb6d/cython3_3.0.11+dfsg-2+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-pexpect all 4.9-3 [55.6 kB] Fetched 55.6 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpfk3cht94/python3-pexpect_4.9-3_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libmpfr6 amd64 4.2.2-1 [729 kB] Fetched 729 kB in 0s (54.5 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpeinc4alv/libmpfr6_4.2.2-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libmpc3 amd64 1.3.1-1+b3 [52.2 kB] Fetched 52.2 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpm3m96hqi/libmpc3_1.3.1-1+b3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3.13-tk amd64 3.13.7-1 [108 kB] Fetched 108 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpr3nmqu_0/python3.13-tk_3.13.7-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 fonts-glyphicons-halflings all 1.009~3.4.1+dfsg-6 [163 kB] Fetched 163 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp4suv2ng7/fonts-glyphicons-halflings_1.009~3.4.1+dfsg-6_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libfribidi0 amd64 1.0.16-1 [26.5 kB] Fetched 26.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp6eno93l6/libfribidi0_1.0.16-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 zlib1g amd64 1:1.3.dfsg+really1.3.1-1+b1 [88.9 kB] Fetched 88.9 kB in 0s (0 B/s) dpkg-name: info: moved 'zlib1g_1%3a1.3.dfsg+really1.3.1-1+b1_amd64.deb' to '/srv/rebuilderd/tmp/tmpvyrfcdm7/zlib1g_1.3.dfsg+really1.3.1-1+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-argon2-cffi-bindings amd64 25.1.0-2 [15.2 kB] Fetched 15.2 kB in 0s (81.6 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp66dkvztw/python3-argon2-cffi-bindings_25.1.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libngtcp2-crypto-gnutls8 amd64 1.11.0-1 [29.3 kB] Fetched 29.3 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp2b4al3_s/libngtcp2-crypto-gnutls8_1.11.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-numpy amd64 1:2.2.4+ds-1 [5096 kB] Fetched 5096 kB in 0s (144 MB/s) dpkg-name: info: moved 'python3-numpy_1%3a2.2.4+ds-1_amd64.deb' to '/srv/rebuilderd/tmp/tmptu8r2wyl/python3-numpy_2.2.4+ds-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libgmp10 amd64 2:6.3.0+dfsg-4 [560 kB] Fetched 560 kB in 0s (47.2 MB/s) dpkg-name: info: moved 'libgmp10_2%3a6.3.0+dfsg-4_amd64.deb' to '/srv/rebuilderd/tmp/tmp0i0u2yia/libgmp10_6.3.0+dfsg-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libc6 amd64 2.41-12 [2846 kB] Fetched 2846 kB in 0s (126 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpvzze7abw/libc6_2.41-12_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 python3-prompt-toolkit all 3.0.52-1 [280 kB] Fetched 280 kB in 0s (27.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpwwbz1jo_/python3-prompt-toolkit_3.0.52-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libacl1 amd64 2.3.2-2+b1 [32.9 kB] Fetched 32.9 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpkx9iqtxt/libacl1_2.3.2-2+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-stringr all 1.5.1-1 [296 kB] Fetched 296 kB in 0s (27.4 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp9kelcf0c/r-cran-stringr_1.5.1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 autoconf all 2.72-3.1 [494 kB] Fetched 494 kB in 0s (42.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp9ealkwos/autoconf_2.72-3.1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-pkgkitten all 0.2.4-1 [29.1 kB] Fetched 29.1 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpt2_6jj5m/r-cran-pkgkitten_0.2.4-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-pytest-forked all 1.6.0-3 [7896 B] Fetched 7896 B in 2s (4471 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmphd3jzafx/python3-pytest-forked_1.6.0-3_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-ipython-genutils all 0.2.0-7 [21.6 kB] Fetched 21.6 kB in 0s (56.2 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpm79a2ujy/python3-ipython-genutils_0.2.0-7_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-matplotlib-inline all 0.1.7-1 [9032 B] Fetched 9032 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpcxhmz6p9/python3-matplotlib-inline_0.1.7-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-docutils all 0.21.2+dfsg-2 [403 kB] Fetched 403 kB in 0s (38.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp_olqm54z/python3-docutils_0.21.2+dfsg-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 libubsan1 amd64 15.2.0-2 [1124 kB] Fetched 1124 kB in 0s (78.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp47axq1mj/libubsan1_15.2.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libamd3 amd64 1:7.11.0+dfsg-1 [49.9 kB] Fetched 49.9 kB in 0s (4769 kB/s) dpkg-name: info: moved 'libamd3_1%3a7.11.0+dfsg-1_amd64.deb' to '/srv/rebuilderd/tmp/tmpnt420kxb/libamd3_7.11.0+dfsg-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libsasl2-2 amd64 2.1.28+dfsg1-9 [57.5 kB] Fetched 57.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp1dg9rn27/libsasl2-2_2.1.28+dfsg1-9_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 libstdc++6 amd64 15.2.0-2 [736 kB] Fetched 736 kB in 0s (56.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpsjqdwtji/libstdc++6_15.2.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-ipython all 8.35.0-1 [576 kB] Fetched 576 kB in 0s (46.0 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpmkysxqs4/python3-ipython_8.35.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libcrypt-dev amd64 1:4.4.38-1 [119 kB] Fetched 119 kB in 0s (0 B/s) dpkg-name: info: moved 'libcrypt-dev_1%3a4.4.38-1_amd64.deb' to '/srv/rebuilderd/tmp/tmpabprcp3a/libcrypt-dev_4.4.38-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-jquery-typeahead all 2.11.0+dfsg1-3 [47.7 kB] Fetched 47.7 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmph746w3mo/libjs-jquery-typeahead_2.11.0+dfsg1-3_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpsl5t64 amd64 0.21.2-1.1+b1 [57.2 kB] Fetched 57.2 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpgyoxem2_/libpsl5t64_0.21.2-1.1+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-cycler all 0.12.1-2 [9616 B] Fetched 9616 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp_rbvmrs4/python3-cycler_0.12.1-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 sed amd64 4.9-2 [329 kB] Fetched 329 kB in 0s (32.5 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp1vgxfr6q/sed_4.9-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 base-files amd64 14 [72.9 kB] Fetched 72.9 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpxsdy9kwo/base-files_14_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 liblz4-1 amd64 1.10.0-4 [63.9 kB] Fetched 63.9 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp0fl4x86f/liblz4-1_1.10.0-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libexpat1-dev amd64 2.7.1-2 [161 kB] Fetched 161 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpr74licez/libexpat1-dev_2.7.1-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjbig0 amd64 2.1-6.1+b2 [32.1 kB] Fetched 32.1 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpvsg38z9w/libjbig0_2.1-6.1+b2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 sphinx-common all 8.2.3-2 [618 kB] Fetched 618 kB in 0s (52.9 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpf2rky603/sphinx-common_8.2.3-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 ncurses-bin amd64 6.5+20250216-2 [438 kB] Fetched 438 kB in 0s (37.8 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpnk7f70rq/ncurses-bin_6.5+20250216-2_amd64.deb' Downloading dependency 1 of 540: libjs-requirejs-text:amd64=2.0.12-1.1 Downloading dependency 2 of 540: libcurl3t64-gnutls:amd64=8.16.0~rc2-1 Downloading dependency 3 of 540: libk5crypto3:amd64=1.21.3-5 Downloading dependency 4 of 540: python3-referencing:amd64=0.36.2-1 Downloading dependency 5 of 540: python3-rpy2:amd64=3.5.17-2 Downloading dependency 6 of 540: fontconfig-config:amd64=2.15.0-2.3 Downloading dependency 7 of 540: python3-zmq:amd64=26.4.0-1 Downloading dependency 8 of 540: python3-nbsphinx:amd64=0.9.5+ds-1 Downloading dependency 9 of 540: dwz:amd64=0.15-1+b1 Downloading dependency 10 of 540: libfile-stripnondeterminism-perl:amd64=1.14.2-1 Downloading dependency 11 of 540: libsodium23:amd64=1.0.18-1+b2 Downloading dependency 12 of 540: libudev1:amd64=258~rc3-1 Downloading dependency 13 of 540: r-cran-littler:amd64=0.3.21-1 Downloading dependency 14 of 540: libsvtav1enc2:amd64=2.3.0+dfsg-1 Downloading dependency 15 of 540: binutils-common:amd64=2.45-4 Downloading dependency 16 of 540: libpipeline1:amd64=1.5.8-1 Downloading dependency 17 of 540: python3-send2trash:amd64=1.8.3-1 Downloading dependency 18 of 540: libtool:amd64=2.5.4-4 Downloading dependency 19 of 540: python3-nest-asyncio:amd64=1.5.4-1 Downloading dependency 20 of 540: r-cran-reformulas:amd64=0.4.1-1 Downloading dependency 21 of 540: r-cran-sp:amd64=1:2.2-0+dfsg-1 Downloading dependency 22 of 540: libipt2:amd64=2.1.2-1 Downloading dependency 23 of 540: g++-14-x86-64-linux-gnu:amd64=14.3.0-5 Downloading dependency 24 of 540: python3-tornado:amd64=6.4.2-3 Downloading dependency 25 of 540: libnuma1:amd64=2.0.19-1 Downloading dependency 26 of 540: 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Downloading dependency 73 of 540: libjs-es6-promise:amd64=4.2.8-12 Downloading dependency 74 of 540: python3-traitlets:amd64=5.14.3+really5.14.3-1 Downloading dependency 75 of 540: r-cran-matrix:amd64=1.7-4-1 Downloading dependency 76 of 540: libgprofng0:amd64=2.45-4 Downloading dependency 77 of 540: python3-sphinx:amd64=8.2.3-2 Downloading dependency 78 of 540: libwebpmux3:amd64=1.5.0-0.1 Downloading dependency 79 of 540: python3-certifi:amd64=2025.1.31+ds-1 Downloading dependency 80 of 540: media-types:amd64=13.0.0 Downloading dependency 81 of 540: libpython3.13-dev:amd64=3.13.7-1 Downloading dependency 82 of 540: tar:amd64=1.35+dfsg-3.1 Downloading dependency 83 of 540: r-cran-dplyr:amd64=1.1.4-4 Downloading dependency 84 of 540: readline-common:amd64=8.3-2 Downloading dependency 85 of 540: xdg-utils:amd64=1.2.1-2 Downloading dependency 86 of 540: libdpkg-perl:amd64=1.22.21 Downloading dependency 87 of 540: libbinutils:amd64=2.45-4 Downloading dependency 88 of 540: libcom-err2:amd64=1.47.2-3+b3 Downloading dependency 89 of 540: python3-yapf:amd64=0.43.0-1 Downloading dependency 90 of 540: cython3:amd64=3.0.11+dfsg-2+b1 Downloading dependency 91 of 540: python3-pexpect:amd64=4.9-3 Downloading dependency 92 of 540: libmpfr6:amd64=4.2.2-1 Downloading dependency 93 of 540: libmpc3:amd64=1.3.1-1+b3 Downloading dependency 94 of 540: python3.13-tk:amd64=3.13.7-1 Downloading dependency 95 of 540: fonts-glyphicons-halflings:amd64=1.009~3.4.1+dfsg-6 Downloading dependency 96 of 540: libfribidi0:amd64=1.0.16-1 Downloading dependency 97 of 540: zlib1g:amd64=1:1.3.dfsg+really1.3.1-1+b1 Downloading dependency 98 of 540: python3-argon2-cffi-bindings:amd64=25.1.0-2 Downloading dependency 99 of 540: libngtcp2-crypto-gnutls8:amd64=1.11.0-1 Downloading dependency 100 of 540: python3-numpy:amd64=1:2.2.4+ds-1 Downloading dependency 101 of 540: libgmp10:amd64=2:6.3.0+dfsg-4 Downloading dependency 102 of 540: libc6:amd64=2.41-12 Downloading dependency 103 of 540: python3-prompt-toolkit:amd64=3.0.52-1 Downloading dependency 104 of 540: libacl1:amd64=2.3.2-2+b1 Downloading dependency 105 of 540: r-cran-stringr:amd64=1.5.1-1 Downloading dependency 106 of 540: autoconf:amd64=2.72-3.1 Downloading dependency 107 of 540: r-cran-pkgkitten:amd64=0.2.4-1 Downloading dependency 108 of 540: python3-pytest-forked:amd64=1.6.0-3 Downloading dependency 109 of 540: python3-ipython-genutils:amd64=0.2.0-7 Downloading dependency 110 of 540: python3-matplotlib-inline:amd64=0.1.7-1 Downloading dependency 111 of 540: python3-docutils:amd64=0.21.2+dfsg-2 Downloading dependency 112 of 540: libubsan1:amd64=15.2.0-2 Downloading dependency 113 of 540: libamd3:amd64=1:7.11.0+dfsg-1 Downloading dependency 114 of 540: libsasl2-2:amd64=2.1.28+dfsg1-9 Downloading dependency 115 of 540: libstdc++6:amd64=15.2.0-2 Downloading dependency 116 of 540: python3-ipython:amd64=8.35.0-1 Downloading dependency 117 of 540: libcrypt-dev:amd64=1:4.4.38-1 Downloading dependency 118 of 540: libjs-jquery-typeahead:amd64=2.11.0+dfsg1-3 Downloading dependency 119 of 540: libpsl5t64:amd64=0.21.2-1.1+b1 Downloading dependency 120 of 540: python3-cycler:amd64=0.12.1-2 Downloading dependency 121 of 540: sed:amd64=4.9-2 Downloading dependency 122 of 540: base-files:amd64=14 Downloading dependency 123 of 540: liblz4-1:amd64=1.10.0-4 Downloading dependency 124 of 540: libexpat1-dev:amd64=2.7.1-2 Downloading dependency 125 of 540: libjbig0:amd64=2.1-6.1+b2 Downloading dependency 126 of 540: sphinx-common:amd64=8.2.3-2 Downloading dependency 127 of 540: ncurses-bin:amd64=6.5+20250216-2 Downloading dependency 128 of 540: python3-ptyprocess:amd64=0.7.0-6Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-ptyprocess all 0.7.0-6 [14.5 kB] Fetched 14.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpbflv8uls/python3-ptyprocess_0.7.0-6_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libldap2 amd64 2.6.10+dfsg-1 [194 kB] Fetched 194 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpa0zed9kx/libldap2_2.6.10+dfsg-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libxcb-render0 amd64 1.17.0-2+b1 [115 kB] Fetched 115 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpvfs_l0f2/libxcb-render0_1.17.0-2+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpython3.13 amd64 3.13.7-1 [2162 kB] Fetched 2162 kB in 0s (111 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpyl8wagdx/libpython3.13_3.13.7-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libnorm1t64 amd64 1.5.9+dfsg-3.1+b2 [221 kB] Fetched 221 kB in 0s (20.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpmm0z1m5n/libnorm1t64_1.5.9+dfsg-3.1+b2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libx11-data all 2:1.8.12-1 [343 kB] Fetched 343 kB in 0s (31.7 MB/s) dpkg-name: info: moved 'libx11-data_2%3a1.8.12-1_all.deb' to '/srv/rebuilderd/tmp/tmpxbf3wt84/libx11-data_1.8.12-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libgdbm6t64 amd64 1.26-1 [78.5 kB] Fetched 78.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpqamyz9qj/libgdbm6t64_1.26-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-nbclient all 0.8.0-3 [62.3 kB] Fetched 62.3 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp4dpawqb_/python3-nbclient_0.8.0-3_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-marked all 4.2.3+ds+~4.0.7-4 [34.7 kB] Fetched 34.7 kB in 0s (234 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmprpeh5w9_/libjs-marked_4.2.3+ds+~4.0.7-4_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-jedi all 0.19.1+ds1-1 [691 kB] Fetched 691 kB in 0s (53.5 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpm8_zgs2j/python3-jedi_0.19.1+ds1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-scipy amd64 1.15.3-1 [16.3 MB] Fetched 16.3 MB in 0s (99.7 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpz4_wlt33/python3-scipy_1.15.3-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 libasan8 amd64 15.2.0-2 [2814 kB] Fetched 2814 kB in 0s (115 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpe37vloei/libasan8_15.2.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-patsy all 1.0.1-1 [172 kB] Fetched 172 kB in 0s (1286 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpk667agk0/python3-patsy_1.0.1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 intltool-debian all 0.35.0+20060710.6 [22.9 kB] Fetched 22.9 kB in 0s (1953 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp6bf7_rmf/intltool-debian_0.35.0+20060710.6_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-coverage amd64 7.8.2+dfsg1-1 [182 kB] Fetched 182 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpwj_4n4sr/python3-coverage_7.8.2+dfsg1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-setuptools all 78.1.1-0.1 [738 kB] Fetched 738 kB in 0s (60.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpg_2hfh5f/python3-setuptools_78.1.1-0.1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libuchardet0 amd64 0.0.8-1+b2 [68.9 kB] Fetched 68.9 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpaabtbufb/libuchardet0_0.0.8-1+b2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-pygments all 2.18.0+dfsg-2 [836 kB] Fetched 836 kB in 0s (64.5 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp_cxhmqyb/python3-pygments_2.18.0+dfsg-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpango-1.0-0 amd64 1.56.3-1 [226 kB] Fetched 226 kB in 0s (19.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp5k9t4uyc/libpango-1.0-0_1.56.3-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-jsonschema-specifications all 2023.12.1-2 [9020 B] Fetched 9020 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpwlrh36_w/python3-jsonschema-specifications_2023.12.1-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 gcc-14 amd64 14.3.0-5 [554 kB] Fetched 554 kB in 0s (44.1 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpjyjrg935/gcc-14_14.3.0-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libdeflate0 amd64 1.23-2 [47.3 kB] Fetched 47.3 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp1tv8o6dl/libdeflate0_1.23-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 debhelper all 13.26 [939 kB] Fetched 939 kB in 0s (66.1 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpsl41gwxa/debhelper_13.26_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 cpp-14 amd64 14.3.0-5 [1276 B] Fetched 1276 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpgot0mja9/cpp-14_14.3.0-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 dpkg-dev all 1.22.21 [1338 kB] Fetched 1338 kB in 0s (78.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpe0nta236/dpkg-dev_1.22.21_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-geepack amd64 1.3.12-1 [387 kB] Fetched 387 kB in 0s (2384 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp6gjo0879/r-cran-geepack_1.3.12-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-withr all 3.0.2+dfsg-1 [226 kB] Fetched 226 kB in 0s (21.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpq8g871zt/r-cran-withr_3.0.2+dfsg-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 linux-libc-dev all 6.16.3-1 [2518 kB] Fetched 2518 kB in 0s (109 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpjnssfutv/linux-libc-dev_6.16.3-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-brotli amd64 1.1.0-2+b7 [320 kB] Fetched 320 kB in 0s (30.8 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpimtyhxbm/python3-brotli_1.1.0-2+b7_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-tinycss2 all 1.4.0-2 [25.0 kB] Fetched 25.0 kB in 0s (2456 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp171soioo/python3-tinycss2_1.4.0-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libproc2-0 amd64 2:4.0.4-9 [65.6 kB] Fetched 65.6 kB in 0s (0 B/s) dpkg-name: info: moved 'libproc2-0_2%3a4.0.4-9_amd64.deb' to '/srv/rebuilderd/tmp/tmpsmyhhkur/libproc2-0_4.0.4-9_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libargon2-1 amd64 0~20190702+dfsg-5 [21.2 kB] Fetched 21.2 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp7t9r9kz5/libargon2-1_0~20190702+dfsg-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpangoft2-1.0-0 amd64 1.56.3-1 [55.6 kB] Fetched 55.6 kB in 0s (5535 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpocvl9u4t/libpangoft2-1.0-0_1.56.3-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libngtcp2-16 amd64 1.11.0-1 [131 kB] Fetched 131 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp3ql3gzle/libngtcp2-16_1.11.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libnlopt0 amd64 2.7.1-6+b4 [178 kB] Fetched 178 kB in 0s (884 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpibkix_ml/libnlopt0_2.7.1-6+b4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libctf-nobfd0 amd64 2.45-4 [157 kB] Fetched 157 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpc8n4t8wq/libctf-nobfd0_2.45-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python-numpy-doc all 1:2.2.4+ds-1 [5814 kB] Fetched 5814 kB in 0s (149 MB/s) dpkg-name: info: moved 'python-numpy-doc_1%3a2.2.4+ds-1_all.deb' to '/srv/rebuilderd/tmp/tmpoin3w44j/python-numpy-doc_2.2.4+ds-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-build all 1.2.2-4 [36.2 kB] Fetched 36.2 kB in 0s (3531 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpuosvzxom/python3-build_1.2.2-4_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 dh-autoreconf all 20 [17.1 kB] Fetched 17.1 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpv__brcwx/dh-autoreconf_20_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-nloptr amd64 2.2.1-2 [254 kB] Fetched 254 kB in 0s (1116 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpczd7ujah/r-cran-nloptr_2.2.1-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 bash amd64 5.2.37-2+b5 [1500 kB] Fetched 1500 kB in 0s (88.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpv74kttf1/bash_5.2.37-2+b5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 libatomic1 amd64 15.2.0-2 [10.7 kB] Fetched 10.7 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpgqd05riv/libatomic1_15.2.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-asttokens all 3.0.0-2 [20.2 kB] Fetched 20.2 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpy0bgupn8/python3-asttokens_3.0.0-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libtiff6 amd64 4.7.0-4 [346 kB] Fetched 346 kB in 0s (33.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmppfwvn34z/libtiff6_4.7.0-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-bootstrap-tour all 0.12.0+dfsg-5 [20.9 kB] Fetched 20.9 kB in 0s (84.8 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpmxt5lkkb/libjs-bootstrap-tour_0.12.0+dfsg-5_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 debianutils amd64 5.23.2 [92.4 kB] Fetched 92.4 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpfxp_vqeh/debianutils_5.23.2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-jupyterlab-pygments all 0.2.2-3 [6096 B] Fetched 6096 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpf4gp2ubd/python3-jupyterlab-pygments_0.2.2-3_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libcholmod5 amd64 1:7.11.0+dfsg-1 [647 kB] Fetched 647 kB in 0s (49.5 MB/s) dpkg-name: info: moved 'libcholmod5_1%3a7.11.0+dfsg-1_amd64.deb' to '/srv/rebuilderd/tmp/tmpbjy1j2gz/libcholmod5_7.11.0+dfsg-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libicu76 amd64 76.1-4 [9722 kB] Fetched 9722 kB in 0s (166 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp1qfcq586/libicu76_76.1-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libgpg-error0 amd64 1.55-2 [88.1 kB] Fetched 88.1 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp2q227b3v/libgpg-error0_1.55-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libctf0 amd64 2.45-4 [89.7 kB] Fetched 89.7 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpc59k0v05/libctf0_2.45-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-tibble amd64 3.2.1+dfsg-3 [425 kB] Fetched 425 kB in 0s (31.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp16ug9gy6/r-cran-tibble_3.2.1+dfsg-3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 cpp-x86-64-linux-gnu amd64 4:14.2.0-1 [4840 B] Fetched 4840 B in 0s (0 B/s) dpkg-name: info: moved 'cpp-x86-64-linux-gnu_4%3a14.2.0-1_amd64.deb' to '/srv/rebuilderd/tmp/tmp_8gqap_y/cpp-x86-64-linux-gnu_14.2.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libselinux1 amd64 3.8.1-1 [84.7 kB] Fetched 84.7 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpo6j1n4ad/libselinux1_3.8.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 liblua5.4-0 amd64 5.4.8-1 [146 kB] Fetched 146 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp1wty0_dx/liblua5.4-0_5.4.8-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libxxhash0 amd64 0.8.3-2 [27.1 kB] Fetched 27.1 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp65580f2k/libxxhash0_0.8.3-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libxml2-16 amd64 2.14.5+dfsg-0.2 [638 kB] Fetched 638 kB in 0s (50.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmppy797qn0/libxml2-16_2.14.5+dfsg-0.2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpam-modules-bin amd64 1.7.0-5 [49.1 kB] Fetched 49.1 kB in 0s (4509 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp_qgfv10k/libpam-modules-bin_1.7.0-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libthai0 amd64 0.1.29-2+b1 [49.4 kB] Fetched 49.4 kB in 0s (4360 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpdhbrm1bd/libthai0_0.1.29-2+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-platformdirs all 4.3.7-1 [16.6 kB] Fetched 16.6 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp6z5jdt2f/python3-platformdirs_4.3.7-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-chardet all 5.2.0+dfsg-2 [108 kB] Fetched 108 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp9siz3a9u/python3-chardet_5.2.0+dfsg-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libopenjp2-7 amd64 2.5.3-2.1 [204 kB] Fetched 204 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpedu1kstl/libopenjp2-7_2.5.3-2.1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python-scipy-doc all 1.15.3-1 [24.6 MB] Fetched 24.6 MB in 0s (53.8 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpj0_xszvz/python-scipy-doc_1.15.3-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 python3-pil.imagetk amd64 11.3.0-1 [81.1 kB] Fetched 81.1 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmptgd21fqx/python3-pil.imagetk_11.3.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libgssapi-krb5-2 amd64 1.21.3-5 [138 kB] Fetched 138 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp98kub3mt/libgssapi-krb5-2_1.21.3-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-parso all 0.8.4-1 [67.8 kB] Fetched 67.8 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpl1njra3v/python3-parso_0.8.4-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 sysvinit-utils amd64 3.14-4 [34.1 kB] Fetched 34.1 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpuwceou4t/sysvinit-utils_3.14-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-cli amd64 3.6.4-1 [1370 kB] Fetched 1370 kB in 0s (88.4 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp7e6r1vit/r-cran-cli_3.6.4-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 unzip amd64 6.0-29 [173 kB] Fetched 173 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpqljg2kku/unzip_6.0-29_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-jupyter-core all 5.7.2-5 [35.3 kB] Fetched 35.3 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmptd8wklhb/python3-jupyter-core_5.7.2-5_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 autotools-dev all 20240727.1 [60.2 kB] Fetched 60.2 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpabnau7ny/autotools-dev_20240727.1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpam0g amd64 1.7.0-5 [69.9 kB] Fetched 69.9 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp86pzxz1d/libpam0g_1.7.0-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python-matplotlib-data all 3.10.1+dfsg1-4 [2737 kB] Fetched 2737 kB in 0s (121 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmprjskhm2j/python-matplotlib-data_3.10.1+dfsg1-4_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-stringi amd64 1.8.4-1+b1 [896 kB] Fetched 896 kB in 0s (70.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpz8yqsvhn/r-cran-stringi_1.8.4-1+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 procps amd64 2:4.0.4-9 [882 kB] Fetched 882 kB in 0s (61.9 MB/s) dpkg-name: info: moved 'procps_2%3a4.0.4-9_amd64.deb' to '/srv/rebuilderd/tmp/tmpfa3_9x54/procps_4.0.4-9_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 librav1e0.7 amd64 0.7.1-9+b2 [946 kB] Fetched 946 kB in 0s (73.0 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmplrrni1ul/librav1e0.7_0.7.1-9+b2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-sphinxdoc all 8.2.3-2 [27.3 kB] Fetched 27.3 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmph6i7hyr1/libjs-sphinxdoc_8.2.3-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libgcrypt20 amd64 1.11.2-2 [865 kB] Fetched 865 kB in 0s (67.4 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmppywtsohn/libgcrypt20_1.11.2-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-purrr amd64 1.0.4-1 [556 kB] Fetched 556 kB in 0s (42.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmptgz35jx8/r-cran-purrr_1.0.4-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-imagesize all 1.4.1-1 [6688 B] Fetched 6688 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp5mv43d60/python3-imagesize_1.4.1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 sgml-base all 1.31+nmu1 [10.9 kB] Fetched 10.9 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpd_hq59ap/sgml-base_1.31+nmu1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-debugpy amd64 1.8.12+ds-1 [751 kB] Fetched 751 kB in 0s (62.0 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp26xygl2b/python3-debugpy_1.8.12+ds-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3.13-minimal amd64 3.13.7-1 [2216 kB] Fetched 2216 kB in 0s (120 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpqkvqzacu/python3.13-minimal_3.13.7-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libsource-highlight-common all 3.1.9-4.3 [77.5 kB] Fetched 77.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp58dgqn7f/libsource-highlight-common_3.1.9-4.3_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 debconf all 1.5.91 [121 kB] Fetched 121 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpo1xj60k6/debconf_1.5.91_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-jaraco.functools all 4.1.0-1 [12.0 kB] Fetched 12.0 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp4wildo_s/python3-jaraco.functools_4.1.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-more-itertools all 10.7.0-1 [67.4 kB] Fetched 67.4 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp21yqn6yk/python3-more-itertools_10.7.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-comm all 0.2.1-1 [8104 B] Fetched 8104 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmppzdxc5y3/python3-comm_0.2.1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-zoo amd64 1.8-14-1 [1001 kB] Fetched 1001 kB in 0s (3987 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp_5g9v123/r-cran-zoo_1.8-14-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 g++-14 amd64 14.3.0-5 [28.2 kB] Fetched 28.2 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpg3nnv0fy/g++-14_14.3.0-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-roman-numerals all 3.1.0-2 [8740 B] Fetched 8740 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp79z1nip4/python3-roman-numerals_3.1.0-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 fonts-open-sans all 1.11-2 [574 kB] Fetched 574 kB in 0s (48.5 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp2fjfxz71/fonts-open-sans_1.11-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-bleach all 6.2.0-1 [51.2 kB] Fetched 51.2 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpglv9crd4/python3-bleach_6.2.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libdb5.3t64 amd64 5.3.28+dfsg2-9 [704 kB] Fetched 704 kB in 0s (57.9 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpig8x9qf0/libdb5.3t64_5.3.28+dfsg2-9_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 g++-x86-64-linux-gnu amd64 4:14.2.0-1 [1200 B] Fetched 1200 B in 0s (0 B/s) dpkg-name: info: moved 'g++-x86-64-linux-gnu_4%3a14.2.0-1_amd64.deb' to '/srv/rebuilderd/tmp/tmpenz_iuc5/g++-x86-64-linux-gnu_14.2.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libabsl20240722 amd64 20240722.0-4 [492 kB] Fetched 492 kB in 0s (40.0 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpzdh68g8j/libabsl20240722_20240722.0-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 man-db amd64 2.13.1-1 [1469 kB] Fetched 1469 kB in 0s (85.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpeds5wylv/man-db_2.13.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libsuitesparseconfig7 amd64 1:7.11.0+dfsg-1 [33.0 kB] Fetched 33.0 kB in 0s (0 B/s) dpkg-name: info: moved 'libsuitesparseconfig7_1%3a7.11.0+dfsg-1_amd64.deb' to '/srv/rebuilderd/tmp/tmpjay3d_6r/libsuitesparseconfig7_7.11.0+dfsg-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libexpat1 amd64 2.7.1-2 [108 kB] Fetched 108 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmprb372er3/libexpat1_2.7.1-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-argon2 amd64 25.1.0-2 [18.2 kB] Fetched 18.2 kB in 1s (16.1 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpohz_9zdp/python3-argon2_25.1.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 libgcc-s1 amd64 15.2.0-2 [75.4 kB] Fetched 75.4 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpz9fq84aw/libgcc-s1_15.2.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libsasl2-modules-db amd64 2.1.28+dfsg1-9 [19.8 kB] Fetched 19.8 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpm84foh7g/libsasl2-modules-db_2.1.28+dfsg1-9_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libimagequant0 amd64 4.4.0-3 [251 kB] Fetched 251 kB in 0s (23.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpwp6lpapj/libimagequant0_4.4.0-3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libsqlite3-0 amd64 3.46.1-7 [914 kB] Fetched 914 kB in 0s (61.9 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmppyriebm7/libsqlite3-0_3.46.1-7_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 python3-requests all 2.32.5+dfsg-1 [72.4 kB] Fetched 72.4 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpifj2ubq9/python3-requests_2.32.5+dfsg-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libxau6 amd64 1:1.0.11-1 [20.4 kB] Fetched 20.4 kB in 0s (0 B/s) dpkg-name: info: moved 'libxau6_1%3a1.0.11-1_amd64.deb' to '/srv/rebuilderd/tmp/tmp29yid6il/libxau6_1.0.11-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 pybuild-plugin-pyproject all 6.20250414 [11.8 kB] Fetched 11.8 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpwglvrlpr/pybuild-plugin-pyproject_6.20250414_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-html5lib all 1.2-2 [92.1 kB] Fetched 92.1 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmprbocubir/python3-html5lib_1.2-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-utf8 amd64 1.2.4-1 [133 kB] Fetched 133 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmphkkgnw7z/r-cran-utf8_1.2.4-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libarchive-zip-perl all 1.68-1 [104 kB] Fetched 104 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpgdfqnq3j/libarchive-zip-perl_1.68-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libtext-wrapi18n-perl all 0.06-10 [8808 B] Fetched 8808 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpcea8_ewt/libtext-wrapi18n-perl_0.06-10_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-requirejs all 2.3.7+ds+~2.1.37-1 [196 kB] Fetched 196 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmprq6u8atn/libjs-requirejs_2.3.7+ds+~2.1.37-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 po-debconf all 1.0.21+nmu1 [248 kB] Fetched 248 kB in 0s (23.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp5sl2i8yd/po-debconf_1.0.21+nmu1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-markupsafe amd64 2.1.5-1+b3 [14.0 kB] Fetched 14.0 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpgj0zg53e/python3-markupsafe_2.1.5-1+b3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 mawk amd64 1.3.4.20250131-1 [141 kB] Fetched 141 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpe8aeuywe/mawk_1.3.4.20250131-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libhogweed6t64 amd64 3.10.1-1 [335 kB] Fetched 335 kB in 0s (31.8 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpxic0b5_j/libhogweed6t64_3.10.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-decorator all 5.2.1-2 [33.0 kB] Fetched 33.0 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp_cjxdv0w/python3-decorator_5.2.1-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libice6 amd64 2:1.1.1-1 [65.4 kB] Fetched 65.4 kB in 0s (0 B/s) dpkg-name: info: moved 'libice6_2%3a1.1.1-1_amd64.deb' to '/srv/rebuilderd/tmp/tmps827kpxe/libice6_1.1.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libharfbuzz0b amd64 10.2.0-1+b1 [479 kB] Fetched 479 kB in 0s (39.4 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpn04oq0dc/libharfbuzz0b_10.2.0-1+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libbrotli1 amd64 1.1.0-2+b7 [307 kB] Fetched 307 kB in 0s (30.0 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpgi_c3shc/libbrotli1_1.1.0-2+b7_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-urllib3 all 2.5.0-1 [116 kB] Fetched 116 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpiq4bu2ms/python3-urllib3_2.5.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libsharpyuv0 amd64 1.5.0-0.1 [116 kB] Fetched 116 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp7eawjxpk/libsharpyuv0_1.5.0-0.1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libsmartcols1 amd64 2.41.1-1 [143 kB] Fetched 143 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp7jvmhjry/libsmartcols1_2.41.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libtirpc-common all 1.3.6+ds-1 [11.0 kB] Fetched 11.0 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpxc4gwoon/libtirpc-common_1.3.6+ds-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpng16-16t64 amd64 1.6.50-1 [282 kB] Fetched 282 kB in 0s (26.7 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpr5341c82/libpng16-16t64_1.6.50-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjson-c5 amd64 0.18+ds-1 [46.0 kB] Fetched 46.0 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpzt3w3rhb/libjson-c5_0.18+ds-1_amd64.deb' Downloading dependency 129 of 540: libldap2:amd64=2.6.10+dfsg-1 Downloading dependency 130 of 540: libxcb-render0:amd64=1.17.0-2+b1 Downloading dependency 131 of 540: libpython3.13:amd64=3.13.7-1 Downloading dependency 132 of 540: libnorm1t64:amd64=1.5.9+dfsg-3.1+b2 Downloading dependency 133 of 540: libx11-data:amd64=2:1.8.12-1 Downloading dependency 134 of 540: libgdbm6t64:amd64=1.26-1 Downloading dependency 135 of 540: python3-nbclient:amd64=0.8.0-3 Downloading dependency 136 of 540: libjs-marked:amd64=4.2.3+ds+~4.0.7-4 Downloading dependency 137 of 540: python3-jedi:amd64=0.19.1+ds1-1 Downloading dependency 138 of 540: python3-scipy:amd64=1.15.3-1 Downloading dependency 139 of 540: libasan8:amd64=15.2.0-2 Downloading dependency 140 of 540: python3-patsy:amd64=1.0.1-1 Downloading dependency 141 of 540: intltool-debian:amd64=0.35.0+20060710.6 Downloading dependency 142 of 540: python3-coverage:amd64=7.8.2+dfsg1-1 Downloading dependency 143 of 540: python3-setuptools:amd64=78.1.1-0.1 Downloading dependency 144 of 540: libuchardet0:amd64=0.0.8-1+b2 Downloading dependency 145 of 540: python3-pygments:amd64=2.18.0+dfsg-2 Downloading dependency 146 of 540: libpango-1.0-0:amd64=1.56.3-1 Downloading dependency 147 of 540: python3-jsonschema-specifications:amd64=2023.12.1-2 Downloading dependency 148 of 540: gcc-14:amd64=14.3.0-5 Downloading dependency 149 of 540: libdeflate0:amd64=1.23-2 Downloading dependency 150 of 540: debhelper:amd64=13.26 Downloading dependency 151 of 540: cpp-14:amd64=14.3.0-5 Downloading dependency 152 of 540: dpkg-dev:amd64=1.22.21 Downloading dependency 153 of 540: r-cran-geepack:amd64=1.3.12-1 Downloading dependency 154 of 540: r-cran-withr:amd64=3.0.2+dfsg-1 Downloading dependency 155 of 540: linux-libc-dev:amd64=6.16.3-1 Downloading dependency 156 of 540: python3-brotli:amd64=1.1.0-2+b7 Downloading dependency 157 of 540: python3-tinycss2:amd64=1.4.0-2 Downloading dependency 158 of 540: libproc2-0:amd64=2:4.0.4-9 Downloading dependency 159 of 540: libargon2-1:amd64=0~20190702+dfsg-5 Downloading dependency 160 of 540: libpangoft2-1.0-0:amd64=1.56.3-1 Downloading dependency 161 of 540: libngtcp2-16:amd64=1.11.0-1 Downloading dependency 162 of 540: libnlopt0:amd64=2.7.1-6+b4 Downloading dependency 163 of 540: libctf-nobfd0:amd64=2.45-4 Downloading dependency 164 of 540: python-numpy-doc:amd64=1:2.2.4+ds-1 Downloading dependency 165 of 540: python3-build:amd64=1.2.2-4 Downloading dependency 166 of 540: dh-autoreconf:amd64=20 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liblua5.4-0:amd64=5.4.8-1 Downloading dependency 183 of 540: libxxhash0:amd64=0.8.3-2 Downloading dependency 184 of 540: libxml2-16:amd64=2.14.5+dfsg-0.2 Downloading dependency 185 of 540: libpam-modules-bin:amd64=1.7.0-5 Downloading dependency 186 of 540: libthai0:amd64=0.1.29-2+b1 Downloading dependency 187 of 540: python3-platformdirs:amd64=4.3.7-1 Downloading dependency 188 of 540: python3-chardet:amd64=5.2.0+dfsg-2 Downloading dependency 189 of 540: libopenjp2-7:amd64=2.5.3-2.1 Downloading dependency 190 of 540: python-scipy-doc:amd64=1.15.3-1 Downloading dependency 191 of 540: python3-pil.imagetk:amd64=11.3.0-1 Downloading dependency 192 of 540: libgssapi-krb5-2:amd64=1.21.3-5 Downloading dependency 193 of 540: python3-parso:amd64=0.8.4-1 Downloading dependency 194 of 540: sysvinit-utils:amd64=3.14-4 Downloading dependency 195 of 540: r-cran-cli:amd64=3.6.4-1 Downloading dependency 196 of 540: unzip:amd64=6.0-29 Downloading dependency 197 of 540: 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242 of 540: mawk:amd64=1.3.4.20250131-1 Downloading dependency 243 of 540: libhogweed6t64:amd64=3.10.1-1 Downloading dependency 244 of 540: python3-decorator:amd64=5.2.1-2 Downloading dependency 245 of 540: libice6:amd64=2:1.1.1-1 Downloading dependency 246 of 540: libharfbuzz0b:amd64=10.2.0-1+b1 Downloading dependency 247 of 540: libbrotli1:amd64=1.1.0-2+b7 Downloading dependency 248 of 540: python3-urllib3:amd64=2.5.0-1 Downloading dependency 249 of 540: libsharpyuv0:amd64=1.5.0-0.1 Downloading dependency 250 of 540: libsmartcols1:amd64=2.41.1-1 Downloading dependency 251 of 540: libtirpc-common:amd64=1.3.6+ds-1 Downloading dependency 252 of 540: libpng16-16t64:amd64=1.6.50-1 Downloading dependency 253 of 540: libjson-c5:amd64=0.18+ds-1 Downloading dependency 254 of 540: libjs-jquery:amd64=3.7.1+dfsg+~3.5.33-1Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-jquery all 3.7.1+dfsg+~3.5.33-1 [319 kB] Fetched 319 kB in 0s (31.7 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp1znzuari/libjs-jquery_3.7.1+dfsg+~3.5.33-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libdatrie1 amd64 0.2.13-4 [38.0 kB] Fetched 38.0 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpaa0z1_05/libdatrie1_0.2.13-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libsystemd0 amd64 258~rc3-1 [465 kB] Fetched 465 kB in 0s (44.0 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp_vq3dtw6/libsystemd0_258~rc3-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libgsl28 amd64 2.8+dfsg-5 [994 kB] Fetched 994 kB in 0s (73.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp8szwufda/libgsl28_2.8+dfsg-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libnettle8t64 amd64 3.10.1-1 [305 kB] Fetched 305 kB in 0s (28.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmphx5m_yow/libnettle8t64_3.10.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 groff-base amd64 1.23.0-9 [1187 kB] Fetched 1187 kB in 0s (83.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpodp4zthl/groff-base_1.23.0-9_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libraqm0 amd64 0.10.3-1 [14.0 kB] Fetched 14.0 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpfzcn8ix6/libraqm0_0.10.3-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 python3-pil amd64 11.3.0-1 [526 kB] Fetched 526 kB in 0s (46.7 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpucrul03_/python3-pil_11.3.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-ufolib2 all 0.17.1+dfsg1-1 [33.0 kB] Fetched 33.0 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpi04yq970/python3-ufolib2_0.17.1+dfsg1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-simplegeneric all 0.8.1-5 [10.9 kB] Fetched 10.9 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp9cwf90wb/python3-simplegeneric_0.8.1-5_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libffi8 amd64 3.4.8-2 [24.1 kB] Fetched 24.1 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpjw4npadl/libffi8_3.4.8-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 blt amd64 2.5.3+dfsg-8 [5984 B] Fetched 5984 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpjj4xns_b/blt_2.5.3+dfsg-8_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 cpp-14-x86-64-linux-gnu amd64 14.3.0-5 [11.0 MB] Fetched 11.0 MB in 0s (169 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpwdr3621n/cpp-14-x86-64-linux-gnu_14.3.0-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpaper-utils amd64 2.2.5-0.3+b2 [16.5 kB] Fetched 16.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp1fwthhsc/libpaper-utils_2.2.5-0.3+b2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libyaml-0-2 amd64 0.2.5-2 [52.5 kB] Fetched 52.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpaqmbcl45/libyaml-0-2_0.2.5-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 node-jed all 1.1.1-4 [14.7 kB] Fetched 14.7 kB in 0s (93.9 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmph34nt_np/node-jed_1.1.1-4_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-rlang amd64 1.1.5-3 [1709 kB] Fetched 1709 kB in 0s (6296 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp3fxook3i/r-cran-rlang_1.1.5-3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 libreadline8t64 amd64 8.3-2 [180 kB] Fetched 180 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp9hyig26s/libreadline8t64_8.3-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-soupsieve all 2.7-2 [39.0 kB] Fetched 39.0 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpi2r1ozxg/python3-soupsieve_2.7-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 libtsan2 amd64 15.2.0-2 [2526 kB] Fetched 2526 kB in 0s (114 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpzgrqggtk/libtsan2_15.2.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libwebp7 amd64 1.5.0-0.1 [318 kB] Fetched 318 kB in 0s (31.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpek_7d87p/libwebp7_1.5.0-0.1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libkeyutils1 amd64 1.6.3-6 [9456 B] Fetched 9456 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp12s00u0v/libkeyutils1_1.6.3-6_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 rpcsvc-proto amd64 1.4.3-1 [63.3 kB] Fetched 63.3 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpk3enq1aq/rpcsvc-proto_1.4.3-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-zopfli amd64 0.2.3.post1-1+b1 [10.5 kB] Fetched 10.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp3wbmbq6_/python3-zopfli_0.2.3.post1-1+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 util-linux amd64 2.41.1-1 [1236 kB] Fetched 1236 kB in 0s (68.1 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpj694qtde/util-linux_2.41.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libavif16 amd64 1.3.0-1 [135 kB] Fetched 135 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpj69k0zsb/libavif16_1.3.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-terminado all 0.18.1-1 [17.3 kB] Fetched 17.3 kB in 0s (76.9 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpv0x71iok/python3-terminado_0.18.1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-base-core amd64 4.5.1-1 [28.7 MB] Fetched 28.7 MB in 1s (46.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpxu8hl8su/r-base-core_4.5.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-xterm all 5.3.0-4 [456 kB] Fetched 456 kB in 0s (1934 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmplnm9vr52/libjs-xterm_5.3.0-4_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libattr1 amd64 1:2.5.2-3 [22.9 kB] Fetched 22.9 kB in 0s (2052 kB/s) dpkg-name: info: moved 'libattr1_1%3a2.5.2-3_amd64.deb' to '/srv/rebuilderd/tmp/tmpwm0i1ts6/libattr1_2.5.2-3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-all amd64 3.13.7-1 [1048 B] Fetched 1048 B in 0s (105 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpp0qwz8qc/python3-all_3.13.7-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 gcc-14-base amd64 14.3.0-5 [51.5 kB] Fetched 51.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpv178w7in/gcc-14-base_14.3.0-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-pandas-lib amd64 2.2.3+dfsg-9 [4595 kB] Fetched 4595 kB in 0s (139 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp6xbfgxbm/python3-pandas-lib_2.2.3+dfsg-9_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-installer all 0.7.0+dfsg1-3 [18.6 kB] Fetched 18.6 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp0nj3zh_1/python3-installer_0.7.0+dfsg1-3_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libxft2 amd64 2.3.6-1+b4 [54.5 kB] Fetched 54.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpu5zp452l/libxft2_2.3.6-1+b4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python-matplotlib-doc all 3.10.1+dfsg1-4 [170 MB] Fetched 170 MB in 5s (34.5 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpxv1xs816/python-matplotlib-doc_3.10.1+dfsg1-4_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libtirpc3t64 amd64 1.3.6+ds-1 [83.3 kB] Fetched 83.3 kB in 0s (0 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skipping '/srv/rebuilderd/tmp/tmpxkhi88yp/libdebconfclient0_0.280_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libaudit-common all 1:4.0.5-1 [13.5 kB] Fetched 13.5 kB in 0s (0 B/s) dpkg-name: info: moved 'libaudit-common_1%3a4.0.5-1_all.deb' to '/srv/rebuilderd/tmp/tmp18x8_tzv/libaudit-common_4.0.5-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libunistring5 amd64 1.3-2 [477 kB] Fetched 477 kB in 0s (43.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpqdkytmld/libunistring5_1.3-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-cardata all 3.0.5-1 [1797 kB] Fetched 1797 kB in 0s (5027 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp0cmdg28k/r-cran-cardata_3.0.5-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpam-runtime all 1.7.0-5 [249 kB] Fetched 249 kB in 0s (22.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpuwnym5tq/libpam-runtime_1.7.0-5_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 pandoc-data all 3.1.11.1-3 [459 kB] Fetched 459 kB in 0s (40.9 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp9lmfh12p/pandoc-data_3.1.11.1-3_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-typeguard all 4.4.4-1 [37.1 kB] Fetched 37.1 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpqg5riaek/python3-typeguard_4.4.4-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libwebpdemux2 amd64 1.5.0-0.1 [113 kB] Fetched 113 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmplamkbt37/libwebpdemux2_1.5.0-0.1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libtasn1-6 amd64 4.20.0-2 [49.9 kB] Fetched 49.9 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp_9d8r22z/libtasn1-6_4.20.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-wcwidth all 0.2.13+dfsg1-1 [24.9 kB] Fetched 24.9 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp45uxdl_x/python3-wcwidth_0.2.13+dfsg1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libcap-ng0 amd64 0.8.5-4+b1 [17.6 kB] Fetched 17.6 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp6ep6qgz9/libcap-ng0_0.8.5-4+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 autopoint all 0.23.1-2 [770 kB] Fetched 770 kB in 0s (63.8 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp34ukdo9d/autopoint_0.23.1-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-guerry all 1.8.3-1 [1289 kB] Fetched 1289 kB in 0s (4771 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpfac3abwt/r-cran-guerry_1.8.3-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-mathjax all 2.7.9+dfsg-1 [5667 kB] Fetched 5667 kB in 0s (157 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp2hfn0epx/libjs-mathjax_2.7.9+dfsg-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 libquadmath0 amd64 15.2.0-2 [149 kB] Fetched 149 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp3zg8iq_w/libquadmath0_15.2.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 fonts-lyx all 2.4.3-1 [190 kB] Fetched 190 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpz41e367f/fonts-lyx_2.4.3-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libcamd3 amd64 1:7.11.0+dfsg-1 [46.7 kB] Fetched 46.7 kB in 0s (0 B/s) dpkg-name: info: moved 'libcamd3_1%3a7.11.0+dfsg-1_amd64.deb' to '/srv/rebuilderd/tmp/tmpc14uil7z/libcamd3_7.11.0+dfsg-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-yaml amd64 6.0.2-2 [137 kB] Fetched 137 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp_r74fns6/python3-yaml_6.0.2-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 m4 amd64 1.4.19-8 [294 kB] Fetched 294 kB in 0s (27.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpe373wiv7/m4_1.4.19-8_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libgdbm-compat4t64 amd64 1.26-1 [52.8 kB] Fetched 52.8 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpq99ddz7l/libgdbm-compat4t64_1.26-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-bs4 all 4.13.4-4 [167 kB] Fetched 167 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpj7heoz9k/python3-bs4_4.13.4-4_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 tk8.6-blt2.5 amd64 2.5.3+dfsg-8 [591 kB] Fetched 591 kB in 0s (49.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp7p82oxc7/tk8.6-blt2.5_2.5.3+dfsg-8_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-fansi amd64 1.0.6-2 [629 kB] Fetched 629 kB in 0s (2983 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp_2my66ms/r-cran-fansi_1.0.6-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libcairo2 amd64 1.18.4-1+b1 [538 kB] Fetched 538 kB in 0s (44.5 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpgf8yj0eo/libcairo2_1.18.4-1+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 automake all 1:1.17-4 [862 kB] Fetched 862 kB in 0s (64.8 MB/s) dpkg-name: info: moved 'automake_1%3a1.17-4_all.deb' to '/srv/rebuilderd/tmp/tmpwjjg69cw/automake_1.17-4_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libgslcblas0 amd64 2.8+dfsg-5 [116 kB] Fetched 116 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp1tv_4hpb/libgslcblas0_2.8+dfsg-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libelf1t64 amd64 0.192-4 [189 kB] Fetched 189 kB in 0s (18.9 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpyy4xhld9/libelf1t64_0.192-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 liblapack3 amd64 3.12.1-6 [2447 kB] Fetched 2447 kB in 0s (113 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp24hkq4l3/liblapack3_3.12.1-6_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libthai-data all 0.1.29-2 [168 kB] Fetched 168 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmphv2pl62h/libthai-data_0.1.29-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 gcc-x86-64-linux-gnu amd64 4:14.2.0-1 [1436 B] Fetched 1436 B in 0s (0 B/s) dpkg-name: info: moved 'gcc-x86-64-linux-gnu_4%3a14.2.0-1_amd64.deb' to '/srv/rebuilderd/tmp/tmpypywv9ej/gcc-x86-64-linux-gnu_14.2.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libtext-charwidth-perl amd64 0.04-11+b4 [9476 B] Fetched 9476 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpkp8wgukt/libtext-charwidth-perl_0.04-11+b4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libp11-kit0 amd64 0.25.5-3 [425 kB] Fetched 425 kB in 0s (38.8 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpwumbvw5a/libp11-kit0_0.25.5-3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 librtmp1 amd64 2.4+20151223.gitfa8646d.1-3 [58.3 kB] Fetched 58.3 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp2ca856z6/librtmp1_2.4+20151223.gitfa8646d.1-3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-pytest all 8.4.1-1 [266 kB] Fetched 266 kB in 0s (22.4 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp2skq27um/python3-pytest_8.4.1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libzopfli1 amd64 1.0.3-3 [106 kB] Fetched 106 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpocw06huj/libzopfli1_1.0.3-3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 x11-common all 1:7.7+24 [217 kB] Fetched 217 kB in 0s (0 B/s) dpkg-name: info: moved 'x11-common_1%3a7.7+24_all.deb' to '/srv/rebuilderd/tmp/tmpgwdc4ym0/x11-common_7.7+24_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-backports amd64 1.5.0-2 [121 kB] Fetched 121 kB in 0s (570 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpqtyww707/r-cran-backports_1.5.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-matplotlib amd64 3.10.1+dfsg1-4 [23.8 MB] Fetched 23.8 MB in 0s (63.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpkbkksp9s/python3-matplotlib_3.10.1+dfsg1-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libzmq5 amd64 4.3.5-1+b3 [283 kB] Fetched 283 kB in 0s (25.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpfypwitcr/libzmq5_4.3.5-1+b3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-moment all 2.29.4+ds-1 [155 kB] Fetched 155 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmprdrxsbsr/libjs-moment_2.29.4+ds-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libglpk40 amd64 5.0-2 [398 kB] Fetched 398 kB in 0s (36.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpqzieqps0/libglpk40_5.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libtk8.6 amd64 8.6.17-1 [794 kB] Fetched 794 kB in 0s (59.7 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp1bfaf648/libtk8.6_8.6.17-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-underscore all 1.13.4~dfsg+~1.11.4-3 [116 kB] Fetched 116 kB in 0s (10.9 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpndlds_ci/libjs-underscore_1.13.4~dfsg+~1.11.4-3_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 findutils amd64 4.10.0-3 [700 kB] Fetched 700 kB in 0s (55.8 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmppi_gz6xi/findutils_4.10.0-3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libxext6 amd64 2:1.3.4-1+b3 [50.4 kB] Fetched 50.4 kB in 0s (0 B/s) dpkg-name: info: moved 'libxext6_2%3a1.3.4-1+b3_amd64.deb' to '/srv/rebuilderd/tmp/tmpv9jfcijg/libxext6_1.3.4-1+b3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 fonts-font-awesome all 5.0.10+really4.7.0~dfsg-4.1 [517 kB] Fetched 517 kB in 0s (44.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpc08c5tp5/fonts-font-awesome_5.0.10+really4.7.0~dfsg-4.1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-fastjsonschema all 2.21.1-1 [22.4 kB] Fetched 22.4 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpezdvdi91/python3-fastjsonschema_2.21.1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 gzip amd64 1.13-1 [138 kB] Fetched 138 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp43av4mel/gzip_1.13-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libglib2.0-0t64 amd64 2.84.4-3 [1518 kB] Fetched 1518 kB in 0s (85.5 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmps_m4yvj5/libglib2.0-0t64_2.84.4-3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-pickleshare all 0.7.5-5 [7600 B] Fetched 7600 B in 0s (637 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp5pfh0oim/python3-pickleshare_0.7.5-5_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 littler all 0.3.21-1 [16.9 kB] Fetched 16.9 kB in 1s (14.0 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpsr8tvtxy/littler_0.3.21-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libaom3 amd64 3.12.1-1 [1871 kB] Fetched 1871 kB in 0s (89.0 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp4ezdcbto/libaom3_3.12.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 ncurses-base all 6.5+20250216-2 [273 kB] Fetched 273 kB in 0s (23.9 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp__l_7jo4/ncurses-base_6.5+20250216-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-seaborn all 0.13.2-5 [215 kB] Fetched 215 kB in 0s (17.0 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp6lwdg61c/python3-seaborn_0.13.2-5_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libcap2 amd64 1:2.75-10+b1 [28.8 kB] Fetched 28.8 kB in 0s (0 B/s) dpkg-name: info: moved 'libcap2_1%3a2.75-10+b1_amd64.deb' to '/srv/rebuilderd/tmp/tmpgbyz5wmc/libcap2_2.75-10+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libkrb5support0 amd64 1.21.3-5 [33.0 kB] Fetched 33.0 kB in 0s (2724 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpz6n0zt3t/libkrb5support0_1.21.3-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 binutils amd64 2.45-4 [266 kB] Fetched 266 kB in 0s (24.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpaxhr6cmg/binutils_2.45-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-backbone all 1.4.1~dfsg+~1.4.15-3 [186 kB] Fetched 186 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpk8innt4k/libjs-backbone_1.4.1~dfsg+~1.4.15-3_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 python3-lxml amd64 6.0.1-1 [1434 kB] Fetched 1434 kB in 0s (82.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpfkwuqmtt/python3-lxml_6.0.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 gcc-14-x86-64-linux-gnu amd64 14.3.0-5 [21.4 MB] Fetched 21.4 MB in 0s (149 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpjlns01qc/gcc-14-x86-64-linux-gnu_14.3.0-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-vcd all 1:1.4-13-1 [1287 kB] Fetched 1287 kB in 0s (4049 kB/s) dpkg-name: info: moved 'r-cran-vcd_1%3a1.4-13-1_all.deb' to '/srv/rebuilderd/tmp/tmpxdxpzhqt/r-cran-vcd_1.4-13-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libbz2-1.0 amd64 1.0.8-6 [37.9 kB] Fetched 37.9 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpk6ln1hwv/libbz2-1.0_1.0.8-6_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-attr all 25.3.0-1 [69.5 kB] Fetched 69.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpz56refy3/python3-attr_25.3.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpangocairo-1.0-0 amd64 1.56.3-1 [35.7 kB] Fetched 35.7 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmprlehtu_v/libpangocairo-1.0-0_1.56.3-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 xml-core all 0.19 [20.1 kB] Fetched 20.1 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpwoflzvwt/xml-core_0.19_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-glue amd64 1.8.0-1 [165 kB] Fetched 165 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpxku5e9ap/r-cran-glue_1.8.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libdsdp-5.8t64 amd64 5.8-10.1 [181 kB] Fetched 181 kB in 0s (895 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp6xngylj7/libdsdp-5.8t64_5.8-10.1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libssh2-1t64 amd64 1.11.1-1 [245 kB] Fetched 245 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpu_z4rsao/libssh2-1t64_1.11.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-alabaster all 0.7.16-0.1 [27.9 kB] Fetched 27.9 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpmht_lwei/python3-alabaster_0.7.16-0.1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-lz4 amd64 4.4.4+dfsg-1 [25.4 kB] Fetched 25.4 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp3oq4sd89/python3-lz4_4.4.4+dfsg-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libsource-highlight4t64 amd64 3.1.9-4.3+b1 [335 kB] Fetched 335 kB in 0s (31.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpz1o46bzz/libsource-highlight4t64_3.1.9-4.3+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 ca-certificates all 20250419 [162 kB] Fetched 162 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpe0suhg1w/ca-certificates_20250419_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 dpkg amd64 1.22.21 [1538 kB] Fetched 1538 kB in 0s (93.5 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpycjk5g_r/dpkg_1.22.21_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-dateutil all 2.9.0-4 [79.4 kB] Fetched 79.4 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmprt81cw5x/python3-dateutil_2.9.0-4_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-ply all 3.11-9 [62.9 kB] Fetched 62.9 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmppeoqe65s/python3-ply_3.11-9_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libperl5.40 amd64 5.40.1-6 [4341 kB] Fetched 4341 kB in 0s (138 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpwvrss_j_/libperl5.40_5.40.1-6_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 liblastlog2-2 amd64 2.41.1-1 [28.6 kB] Fetched 28.6 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpsxkaa989/liblastlog2-2_2.41.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libmagic1t64 amd64 1:5.46-5 [109 kB] Fetched 109 kB in 0s (0 B/s) dpkg-name: info: moved 'libmagic1t64_1%3a5.46-5_amd64.deb' to '/srv/rebuilderd/tmp/tmp5qr5lz6q/libmagic1t64_5.46-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-prometheus-client all 0.21.1+ds1-1 [44.9 kB] Fetched 44.9 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpcyx_7lv4/python3-prometheus-client_0.21.1+ds1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libdebhelper-perl all 13.26 [91.8 kB] Fetched 91.8 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpsfubif88/libdebhelper-perl_13.26_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libxcb-shm0 amd64 1.17.0-2+b1 [105 kB] Fetched 105 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp06s_lfcx/libxcb-shm0_1.17.0-2+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libbabeltrace1 amd64 1.5.11-4+b2 [176 kB] Fetched 176 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpujawb36o/libbabeltrace1_1.5.11-4+b2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpython3-all-dev amd64 3.13.7-1 [1068 B] Fetched 1068 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpwbgnnexl/libpython3-all-dev_3.13.7-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpython3.13-stdlib amd64 3.13.7-1 [1960 kB] Fetched 1960 kB in 0s (102 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp0z754_5w/libpython3.13-stdlib_3.13.7-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 make amd64 4.4.1-2 [463 kB] Fetched 463 kB in 0s (43.1 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpcakcyc7p/make_4.4.1-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libmagic-mgc amd64 1:5.46-5 [338 kB] Fetched 338 kB in 0s (0 B/s) dpkg-name: info: moved 'libmagic-mgc_1%3a5.46-5_amd64.deb' to '/srv/rebuilderd/tmp/tmp5lfumrhb/libmagic-mgc_5.46-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-mass amd64 7.3-65-1 [1113 kB] Fetched 1113 kB in 0s (82.5 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpw465hs2e/r-cran-mass_7.3-65-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-vctrs amd64 0.6.5-1 [1375 kB] Fetched 1375 kB in 0s (92.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpgd9mr5rb/r-cran-vctrs_0.6.5-1_amd64.deb' Downloading dependency 255 of 540: libdatrie1:amd64=0.2.13-4 Downloading dependency 256 of 540: libsystemd0:amd64=258~rc3-1 Downloading dependency 257 of 540: libgsl28:amd64=2.8+dfsg-5 Downloading dependency 258 of 540: libnettle8t64:amd64=3.10.1-1 Downloading dependency 259 of 540: groff-base:amd64=1.23.0-9 Downloading dependency 260 of 540: libraqm0:amd64=0.10.3-1 Downloading dependency 261 of 540: python3-pil:amd64=11.3.0-1 Downloading dependency 262 of 540: python3-ufolib2:amd64=0.17.1+dfsg1-1 Downloading dependency 263 of 540: python3-simplegeneric:amd64=0.8.1-5 Downloading dependency 264 of 540: libffi8:amd64=3.4.8-2 Downloading dependency 265 of 540: blt:amd64=2.5.3+dfsg-8 Downloading dependency 266 of 540: cpp-14-x86-64-linux-gnu:amd64=14.3.0-5 Downloading dependency 267 of 540: libpaper-utils:amd64=2.2.5-0.3+b2 Downloading dependency 268 of 540: libyaml-0-2:amd64=0.2.5-2 Downloading dependency 269 of 540: node-jed:amd64=1.1.1-4 Downloading dependency 270 of 540: r-cran-rlang:amd64=1.1.5-3 Downloading dependency 271 of 540: libreadline8t64:amd64=8.3-2 Downloading dependency 272 of 540: python3-soupsieve:amd64=2.7-2 Downloading dependency 273 of 540: libtsan2:amd64=15.2.0-2 Downloading dependency 274 of 540: libwebp7:amd64=1.5.0-0.1 Downloading dependency 275 of 540: libkeyutils1:amd64=1.6.3-6 Downloading dependency 276 of 540: rpcsvc-proto:amd64=1.4.3-1 Downloading dependency 277 of 540: python3-zopfli:amd64=0.2.3.post1-1+b1 Downloading dependency 278 of 540: util-linux:amd64=2.41.1-1 Downloading dependency 279 of 540: libavif16:amd64=1.3.0-1 Downloading dependency 280 of 540: python3-terminado:amd64=0.18.1-1 Downloading dependency 281 of 540: r-base-core:amd64=4.5.1-1 Downloading dependency 282 of 540: libjs-xterm:amd64=5.3.0-4 Downloading dependency 283 of 540: libattr1:amd64=1:2.5.2-3 Downloading dependency 284 of 540: python3-all:amd64=3.13.7-1 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tk8.6-blt2.5:amd64=2.5.3+dfsg-8 Downloading dependency 316 of 540: r-cran-fansi:amd64=1.0.6-2 Downloading dependency 317 of 540: libcairo2:amd64=1.18.4-1+b1 Downloading dependency 318 of 540: automake:amd64=1:1.17-4 Downloading dependency 319 of 540: libgslcblas0:amd64=2.8+dfsg-5 Downloading dependency 320 of 540: libelf1t64:amd64=0.192-4 Downloading dependency 321 of 540: liblapack3:amd64=3.12.1-6 Downloading dependency 322 of 540: libthai-data:amd64=0.1.29-2 Downloading dependency 323 of 540: gcc-x86-64-linux-gnu:amd64=4:14.2.0-1 Downloading dependency 324 of 540: libtext-charwidth-perl:amd64=0.04-11+b4 Downloading dependency 325 of 540: libp11-kit0:amd64=0.25.5-3 Downloading dependency 326 of 540: librtmp1:amd64=2.4+20151223.gitfa8646d.1-3 Downloading dependency 327 of 540: python3-pytest:amd64=8.4.1-1 Downloading dependency 328 of 540: libzopfli1:amd64=1.0.3-3 Downloading dependency 329 of 540: x11-common:amd64=1:7.7+24 Downloading dependency 330 of 540: 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libaom3:amd64=3.12.1-1 Downloading dependency 346 of 540: ncurses-base:amd64=6.5+20250216-2 Downloading dependency 347 of 540: python3-seaborn:amd64=0.13.2-5 Downloading dependency 348 of 540: libcap2:amd64=1:2.75-10+b1 Downloading dependency 349 of 540: libkrb5support0:amd64=1.21.3-5 Downloading dependency 350 of 540: binutils:amd64=2.45-4 Downloading dependency 351 of 540: libjs-backbone:amd64=1.4.1~dfsg+~1.4.15-3 Downloading dependency 352 of 540: python3-lxml:amd64=6.0.1-1 Downloading dependency 353 of 540: gcc-14-x86-64-linux-gnu:amd64=14.3.0-5 Downloading dependency 354 of 540: r-cran-vcd:amd64=1:1.4-13-1 Downloading dependency 355 of 540: libbz2-1.0:amd64=1.0.8-6 Downloading dependency 356 of 540: python3-attr:amd64=25.3.0-1 Downloading dependency 357 of 540: libpangocairo-1.0-0:amd64=1.56.3-1 Downloading dependency 358 of 540: xml-core:amd64=0.19 Downloading dependency 359 of 540: r-cran-glue:amd64=1.8.0-1 Downloading dependency 360 of 540: libdsdp-5.8t64:amd64=5.8-10.1 Downloading dependency 361 of 540: libssh2-1t64:amd64=1.11.1-1 Downloading dependency 362 of 540: python3-alabaster:amd64=0.7.16-0.1 Downloading dependency 363 of 540: python3-lz4:amd64=4.4.4+dfsg-1 Downloading dependency 364 of 540: libsource-highlight4t64:amd64=3.1.9-4.3+b1 Downloading dependency 365 of 540: ca-certificates:amd64=20250419 Downloading dependency 366 of 540: dpkg:amd64=1.22.21 Downloading dependency 367 of 540: python3-dateutil:amd64=2.9.0-4 Downloading dependency 368 of 540: python3-ply:amd64=3.11-9 Downloading dependency 369 of 540: libperl5.40:amd64=5.40.1-6 Downloading dependency 370 of 540: liblastlog2-2:amd64=2.41.1-1 Downloading dependency 371 of 540: libmagic1t64:amd64=1:5.46-5 Downloading dependency 372 of 540: python3-prometheus-client:amd64=0.21.1+ds1-1 Downloading dependency 373 of 540: libdebhelper-perl:amd64=13.26 Downloading dependency 374 of 540: libxcb-shm0:amd64=1.17.0-2+b1 Downloading dependency 375 of 540: libbabeltrace1:amd64=1.5.11-4+b2 Downloading dependency 376 of 540: libpython3-all-dev:amd64=3.13.7-1 Downloading dependency 377 of 540: libpython3.13-stdlib:amd64=3.13.7-1 Downloading dependency 378 of 540: make:amd64=4.4.1-2 Downloading dependency 379 of 540: libmagic-mgc:amd64=1:5.46-5 Downloading dependency 380 of 540: r-cran-mass:amd64=7.3-65-1 Downloading dependency 381 of 540: r-cran-vctrs:amd64=0.6.5-1 Downloading dependency 382 of 540: gcc:amd64=4:14.2.0-1Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 gcc amd64 4:14.2.0-1 [5136 B] Fetched 5136 B in 0s (0 B/s) dpkg-name: info: moved 'gcc_4%3a14.2.0-1_amd64.deb' to '/srv/rebuilderd/tmp/tmpi79q2ddq/gcc_14.2.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-colorama all 0.4.6-4 [36.2 kB] Fetched 36.2 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpv87zsumx/python3-colorama_0.4.6-4_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libstdc++-14-dev amd64 14.3.0-5 [2651 kB] Fetched 2651 kB in 0s (121 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpf6subqrh/libstdc++-14-dev_14.3.0-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 zlib1g-dev amd64 1:1.3.dfsg+really1.3.1-1+b1 [920 kB] Fetched 920 kB in 0s (68.5 MB/s) dpkg-name: info: moved 'zlib1g-dev_1%3a1.3.dfsg+really1.3.1-1+b1_amd64.deb' to '/srv/rebuilderd/tmp/tmp9ypfiu_4/zlib1g-dev_1.3.dfsg+really1.3.1-1+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 build-essential amd64 12.12 [4624 B] Fetched 4624 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmptse76dur/build-essential_12.12_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libfontconfig1 amd64 2.15.0-2.3 [392 kB] Fetched 392 kB in 0s (31.9 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmplvosh516/libfontconfig1_2.15.0-2.3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpython3-dev amd64 3.13.7-1 [10.5 kB] Fetched 10.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp2298gbej/libpython3-dev_3.13.7-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libdebuginfod-common all 0.192-4 [23.7 kB] Fetched 23.7 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpp9978g1r/libdebuginfod-common_0.192-4_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-defusedxml all 0.7.1-3 [43.4 kB] Fetched 43.4 kB in 0s (4099 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpdzj4__ds/python3-defusedxml_0.7.1-3_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 liblsan0 amd64 15.2.0-2 [1266 kB] Fetched 1266 kB in 0s (76.5 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpfwcy4zrh/liblsan0_15.2.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python-tinycss2-common all 1.4.0-2 [44.7 kB] Fetched 44.7 kB in 0s (4313 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpjl7n7jby/python-tinycss2-common_1.4.0-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 gettext amd64 0.23.1-2+b1 [1680 kB] Fetched 1680 kB in 0s (98.7 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpo0lmm67l/gettext_0.23.1-2+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-ipykernel all 6.30.1-1 [104 kB] Fetched 104 kB in 0s (7691 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpunyvc1f8/python3-ipykernel_6.30.1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-pycparser all 2.22-2 [78.0 kB] Fetched 78.0 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpkbe4k3ez/python3-pycparser_2.22-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-notebook all 6.4.13-5 [1537 kB] Fetched 1537 kB in 0s (4554 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpd4j0gkyb/python3-notebook_6.4.13-5_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjansson4 amd64 2.14-2+b3 [39.8 kB] Fetched 39.8 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpyqrv0un5/libjansson4_2.14-2+b3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-sympy all 1.14.0-2 [4228 kB] Fetched 4228 kB in 0s (138 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmptahud18b/python3-sympy_1.14.0-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libltdl7 amd64 2.5.4-4 [416 kB] Fetched 416 kB in 0s (38.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpyjd6ewa4/libltdl7_2.5.4-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 libhwasan0 amd64 15.2.0-2 [1559 kB] Fetched 1559 kB in 0s (92.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp24b_2zsu/libhwasan0_15.2.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 gdb amd64 16.3-4 [3958 kB] Fetched 3958 kB in 0s (141 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpvwf4f1xu/gdb_16.3-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 init-system-helpers all 1.69 [39.3 kB] Fetched 39.3 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmprg5zhhyd/init-system-helpers_1.69_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-statmod amd64 1.5.0-1 [295 kB] Fetched 295 kB in 0s (1379 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpsnavmjb3/r-cran-statmod_1.5.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 bsdutils amd64 1:2.41.1-1 [110 kB] Fetched 110 kB in 0s (0 B/s) dpkg-name: info: moved 'bsdutils_1%3a2.41.1-1_amd64.deb' to '/srv/rebuilderd/tmp/tmpgejqtcxy/bsdutils_2.41.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-pandocfilters all 1.5.1-1 [23.7 kB] Fetched 23.7 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpxsfru_og/python3-pandocfilters_1.5.1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-py all 1.11.0-5 [88.9 kB] Fetched 88.9 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpmm9dxyyp/python3-py_1.11.0-5_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 cpp amd64 4:14.2.0-1 [1568 B] Fetched 1568 B in 0s (0 B/s) dpkg-name: info: moved 'cpp_4%3a14.2.0-1_amd64.deb' to '/srv/rebuilderd/tmp/tmpivgix8xj/cpp_14.2.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-kiwisolver amd64 1.4.7-3+b1 [62.0 kB] Fetched 62.0 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpo9gs39vb/python3-kiwisolver_1.4.7-3+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libxt6t64 amd64 1:1.2.1-1.2+b2 [188 kB] Fetched 188 kB in 0s (0 B/s) dpkg-name: info: moved 'libxt6t64_1%3a1.2.1-1.2+b2_amd64.deb' to '/srv/rebuilderd/tmp/tmp0zd4wyap/libxt6t64_1.2.1-1.2+b2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-r6 all 2.6.1-1 [106 kB] Fetched 106 kB in 0s (10.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpnv4kvrr0/r-cran-r6_2.6.1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-contourpy amd64 1.3.1-2 [215 kB] Fetched 215 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp_s9v7383/python3-contourpy_1.3.1-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libuuid1 amd64 2.41.1-1 [37.7 kB] Fetched 37.7 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmptzb0jq2c/libuuid1_2.41.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjodycode3t64 amd64 3.1.2-1 [18.6 kB] Fetched 18.6 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpfbat1u2n/libjodycode3t64_3.1.2-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libmd0 amd64 1.1.0-2+b1 [36.3 kB] Fetched 36.3 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp7lzf5u4c/libmd0_1.1.0-2+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 fonts-dejavu-core all 2.37-8 [840 kB] Fetched 840 kB in 0s (65.4 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp6uuv55yg/fonts-dejavu-core_2.37-8_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 libgfortran5 amd64 15.2.0-2 [893 kB] Fetched 893 kB in 0s (64.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpiolmtowr/libgfortran5_15.2.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libyuv0 amd64 0.0.1916.20250814-1 [172 kB] Fetched 172 kB in 0s (16.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpb0senl4y/libyuv0_0.0.1916.20250814-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libnghttp3-9 amd64 1.8.0-1 [67.7 kB] Fetched 67.7 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpst5v9jmr/libnghttp3-9_1.8.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libzstd1 amd64 1.5.7+dfsg-1 [304 kB] Fetched 304 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpevgmfq2_/libzstd1_1.5.7+dfsg-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 zip amd64 3.0-15 [235 kB] Fetched 235 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpx1eesnou/zip_3.0-15_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libdw1t64 amd64 0.192-4 [255 kB] Fetched 255 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpoc7n16r5/libdw1t64_0.192-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-fonttools amd64 4.57.0-1 [1438 kB] Fetched 1438 kB in 0s (95.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpq_rw7d9a/python3-fonttools_4.57.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-wheel all 0.46.1-2 [21.7 kB] Fetched 21.7 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmplb9bhax0/python3-wheel_0.46.1-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libxdmcp6 amd64 1:1.1.5-1 [27.8 kB] Fetched 27.8 kB in 0s (0 B/s) dpkg-name: info: moved 'libxdmcp6_1%3a1.1.5-1_amd64.deb' to '/srv/rebuilderd/tmp/tmpie193s4g/libxdmcp6_1.1.5-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libumfpack6 amd64 1:7.11.0+dfsg-1 [289 kB] Fetched 289 kB in 0s (0 B/s) dpkg-name: info: moved 'libumfpack6_1%3a7.11.0+dfsg-1_amd64.deb' to '/srv/rebuilderd/tmp/tmpu6y09z7o/libumfpack6_7.11.0+dfsg-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 liblcms2-2 amd64 2.16-2 [160 kB] Fetched 160 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpaiv31aeq/liblcms2-2_2.16-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-bootstrap all 3.4.1+dfsg-6 [173 kB] Fetched 173 kB in 0s (13.0 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpdzu123f_/libjs-bootstrap_3.4.1+dfsg-6_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 diffutils amd64 1:3.10-4 [387 kB] Fetched 387 kB in 0s (38.1 MB/s) dpkg-name: info: moved 'diffutils_1%3a3.10-4_amd64.deb' to '/srv/rebuilderd/tmp/tmp3t5zx0he/diffutils_3.10-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-magrittr amd64 2.0.3-1 [201 kB] Fetched 201 kB in 0s (19.7 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpji3vlnwj/r-cran-magrittr_2.0.3-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-lme4 amd64 1.1-37-1 [4123 kB] Fetched 4123 kB in 1s (3288 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpnoz5hgl1/r-cran-lme4_1.1-37-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-cvxopt amd64 1.3.0+dfsg-1+b9 [265 kB] Fetched 265 kB in 1s (197 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp06j3_x3i/python3-cvxopt_1.3.0+dfsg-1+b9_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-numpydoc all 1.9.0-1 [52.3 kB] Fetched 52.3 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpbdmwoj5m/python3-numpydoc_1.9.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 pandoc amd64 3.1.11.1+ds-3 [26.4 MB] Fetched 26.4 MB in 0s (68.9 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp9y8yt75l/pandoc_3.1.11.1+ds-3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-minimal amd64 3.13.7-1 [27.2 kB] Fetched 27.2 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpinxf49nw/python3-minimal_3.13.7-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libaudit1 amd64 1:4.0.5-1 [59.4 kB] Fetched 59.4 kB in 0s (0 B/s) dpkg-name: info: moved 'libaudit1_1%3a4.0.5-1_amd64.deb' to '/srv/rebuilderd/tmp/tmprny6qruf/libaudit1_4.0.5-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libc-dev-bin amd64 2.41-12 [58.2 kB] Fetched 58.2 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp_r9mmfpz/libc-dev-bin_2.41-12_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 tzdata all 2025b-5 [260 kB] Fetched 260 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmptzkciuz4/tzdata_2025b-5_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-jaraco.context all 6.0.1-1 [8276 B] Fetched 8276 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp68s1ornx/python3-jaraco.context_6.0.1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libxss1 amd64 1:1.2.3-1+b3 [17.0 kB] Fetched 17.0 kB in 0s (0 B/s) dpkg-name: info: moved 'libxss1_1%3a1.2.3-1+b3_amd64.deb' to '/srv/rebuilderd/tmp/tmp7aiioky0/libxss1_1.2.3-1+b3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-autocommand all 2.2.2-3 [13.6 kB] Fetched 13.6 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpafvx0d47/python3-autocommand_2.2.2-3_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-pkgconfig all 2.0.3-2 [19.6 kB] Fetched 19.6 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpxz9_s0g9/r-cran-pkgconfig_2.0.3-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-cpp11 all 0.5.2-1 [226 kB] Fetched 226 kB in 0s (21.8 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp32e2romj/r-cran-cpp11_0.5.2-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-pyparsing all 3.1.2-1 [146 kB] Fetched 146 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpqmp2ilmr/python3-pyparsing_3.1.2-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 fonts-dejavu-mono all 2.37-8 [489 kB] Fetched 489 kB in 0s (44.5 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp3or2u6kw/fonts-dejavu-mono_2.37-8_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 base-passwd amd64 3.6.7 [53.7 kB] Fetched 53.7 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpaqful97l/base-passwd_3.6.7_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 perl amd64 5.40.1-6 [267 kB] Fetched 267 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp_e8fhq5g/perl_5.40.1-6_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-packaging all 25.0-1 [56.6 kB] Fetched 56.6 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmph3by4gqv/python3-packaging_25.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libccolamd3 amd64 1:7.11.0+dfsg-1 [48.6 kB] Fetched 48.6 kB in 0s (0 B/s) dpkg-name: info: moved 'libccolamd3_1%3a7.11.0+dfsg-1_amd64.deb' to '/srv/rebuilderd/tmp/tmp370anhb5/libccolamd3_7.11.0+dfsg-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-dev amd64 3.13.7-1 [26.1 kB] Fetched 26.1 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpw86e_2kg/python3-dev_3.13.7-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 netbase all 6.5 [12.4 kB] Fetched 12.4 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpr8wt86rn/netbase_6.5_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 dash amd64 0.5.12-12 [98.5 kB] Fetched 98.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpzc22tfxe/dash_0.5.12-12_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 dh-strip-nondeterminism all 1.14.2-1 [8768 B] Fetched 8768 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp3tf541w5/dh-strip-nondeterminism_1.14.2-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3.13-doc all 3.13.7-1 [15.5 MB] Fetched 15.5 MB in 0s (103 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpg2zd_sq_/python3.13-doc_3.13.7-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 ucf all 3.0052 [43.3 kB] Fetched 43.3 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp35no0ln6/ucf_3.0052_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-tidyselect amd64 1.2.1+dfsg-1 [223 kB] Fetched 223 kB in 0s (16.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp27hcp5be/r-cran-tidyselect_1.2.1+dfsg-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libdav1d7 amd64 1.5.1-1 [559 kB] Fetched 559 kB in 0s (48.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpwfp8470l/libdav1d7_1.5.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-pkg-resources all 78.1.1-0.1 [224 kB] Fetched 224 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpfsmld6r_/python3-pkg-resources_78.1.1-0.1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-typeshed all 0.0~git20241223.ea91db2-3 [1531 kB] Fetched 1531 kB in 0s (85.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpa90yr8px/python3-typeshed_0.0~git20241223.ea91db2-3_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-jed all 1.1.1-4 [3772 B] Fetched 3772 B in 0s (20.7 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpyinx9ja6/libjs-jed_1.1.1-4_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libssl3t64 amd64 3.5.2-1 [2438 kB] Fetched 2438 kB in 0s (117 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpv3bv3ez4/libssl3t64_3.5.2-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-charset-normalizer amd64 3.4.3-1 [131 kB] Fetched 131 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpsvagt2q6/python3-charset-normalizer_3.4.3-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 xz-utils amd64 5.8.1-1 [660 kB] Fetched 660 kB in 0s (53.1 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmphwxvif7h/xz-utils_5.8.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpcre2-8-0 amd64 10.45-1 [298 kB] Fetched 298 kB in 0s (29.7 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp73j71sk1/libpcre2-8-0_10.45-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libcolamd3 amd64 1:7.11.0+dfsg-1 [41.8 kB] Fetched 41.8 kB in 0s (0 B/s) dpkg-name: info: moved 'libcolamd3_1%3a7.11.0+dfsg-1_amd64.deb' to '/srv/rebuilderd/tmp/tmpsdq6g50r/libcolamd3_7.11.0+dfsg-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 libitm1 amd64 15.2.0-2 [29.7 kB] Fetched 29.7 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpeeda6ym8/libitm1_15.2.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 openssl-provider-legacy amd64 3.5.2-1 [307 kB] Fetched 307 kB in 0s (29.8 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp3iz0f2ol/openssl-provider-legacy_3.5.2-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-all-dev amd64 3.13.7-1 [1068 B] Fetched 1068 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpx8h9it49/python3-all-dev_3.13.7-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 gettext-base amd64 0.23.1-2+b1 [244 kB] Fetched 244 kB in 0s (23.0 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpm23424_9/gettext-base_0.23.1-2+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libmount1 amd64 2.41.1-1 [209 kB] Fetched 209 kB in 0s (20.1 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmprl7c3s4o/libmount1_2.41.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-pure-eval all 0.2.3-1 [11.2 kB] Fetched 11.2 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp0lgbnn4q/python3-pure-eval_0.2.3-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python-pandas-doc all 2.2.3+dfsg-9 [10.8 MB] Fetched 10.8 MB in 0s (139 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpli0cyjny/python-pandas-doc_2.2.3+dfsg-9_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-rbibutils amd64 2.3-1 [948 kB] Fetched 948 kB in 0s (5943 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpjwn9s_4c/r-cran-rbibutils_2.3-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-roman all 5.1-1 [11.0 kB] Fetched 11.0 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp4_unfnfq/python3-roman_5.1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 libgomp1 amd64 15.2.0-2 [152 kB] Fetched 152 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp4p214spc/libgomp1_15.2.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpython3-stdlib amd64 3.13.7-1 [10.2 kB] Fetched 10.2 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpotkyac_k/libpython3-stdlib_3.13.7-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-lmtest amd64 0.9.40-1 [399 kB] Fetched 399 kB in 0s (1463 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmptuum_o0d/r-cran-lmtest_0.9.40-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 fontconfig amd64 2.15.0-2.3 [463 kB] Fetched 463 kB in 0s (42.7 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpdm8cguah/fontconfig_2.15.0-2.3_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libtcl8.6 amd64 8.6.17+dfsg-1 [1041 kB] Fetched 1041 kB in 0s (74.0 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpkueeyfs1/libtcl8.6_8.6.17+dfsg-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-joblib all 1.4.2-5 [216 kB] Fetched 216 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmphhprqjcm/python3-joblib_1.4.2-5_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-rpds-py amd64 0.21.0-2+b1 [257 kB] Fetched 257 kB in 0s (21.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpxzchl_at/python3-rpds-py_0.21.0-2+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-broom all 1.0.7+dfsg-1 [1846 kB] Fetched 1846 kB in 0s (9417 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpkpagtupn/r-cran-broom_1.0.7+dfsg-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libblas3 amd64 3.12.1-6 [160 kB] Fetched 160 kB in 0s (15.8 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpr_y946h8/libblas3_3.12.1-6_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 binutils-x86-64-linux-gnu amd64 2.45-4 [1042 kB] Fetched 1042 kB in 0s (74.8 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpcbqc37o0/binutils-x86-64-linux-gnu_2.45-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libblkid1 amd64 2.41.1-1 [171 kB] Fetched 171 kB in 0s (16.8 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpv20_7m75/libblkid1_2.41.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libcrypt1 amd64 1:4.4.38-1 [90.1 kB] Fetched 90.1 kB in 0s (0 B/s) dpkg-name: info: moved 'libcrypt1_1%3a4.4.38-1_amd64.deb' to '/srv/rebuilderd/tmp/tmpopz52vxp/libcrypt1_4.4.38-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-text-encoding all 0.7.0-5 [104 kB] Fetched 104 kB in 0s (214 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpnth4ept4/libjs-text-encoding_0.7.0-5_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libfreetype6 amd64 2.13.3+dfsg-1 [452 kB] Fetched 452 kB in 0s (41.1 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpznh_ey9o/libfreetype6_2.13.3+dfsg-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 grep amd64 3.11-4 [431 kB] Fetched 431 kB in 0s (37.4 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp0_f2p5b2/grep_3.11-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 jdupes amd64 1.28.0-1 [64.2 kB] Fetched 64.2 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmprj88fm59/jdupes_1.28.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-boot all 1.3-31-1 [639 kB] Fetched 639 kB in 0s (56.7 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp8pimsdzg/r-cran-boot_1.3-31-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-pillar all 1.10.1+dfsg-1 [453 kB] Fetched 453 kB in 0s (42.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp15xomg70/r-cran-pillar_1.10.1+dfsg-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 hostname amd64 3.25 [11.0 kB] Fetched 11.0 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpt_4zai20/hostname_3.25_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-iniconfig all 1.1.1-2 [6396 B] Fetched 6396 B in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp94ce6gn5/python3-iniconfig_1.1.1-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-rcpp amd64 1.1.0-1 [2114 kB] Fetched 2114 kB in 0s (12.9 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpqt0ki9r6/r-cran-rcpp_1.1.0-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3.13 amd64 3.13.7-1 [761 kB] Fetched 761 kB in 0s (59.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmphqooxmrp/python3.13_3.13.7-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-tk amd64 3.13.5-1 [9604 B] Fetched 9604 B in 0s (921 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp_5f9k05s/python3-tk_3.13.5-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 openssl amd64 3.5.2-1 [1493 kB] Fetched 1493 kB in 0s (89.0 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpnehkfzst/openssl_3.5.2-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-cffi all 2.0.0~b1-1 [90.3 kB] Fetched 90.3 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmppqtiu9fk/python3-cffi_2.0.0~b1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-lifecycle all 1.0.4+dfsg-1 [110 kB] Fetched 110 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpor02yys9/r-cran-lifecycle_1.0.4+dfsg-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libx11-6 amd64 2:1.8.12-1 [815 kB] Fetched 815 kB in 0s (66.6 MB/s) dpkg-name: info: moved 'libx11-6_2%3a1.8.12-1_amd64.deb' to '/srv/rebuilderd/tmp/tmp58ncjf_m/libx11-6_1.8.12-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 bzip2 amd64 1.0.8-6 [40.5 kB] Fetched 40.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmptj_xkmvj/bzip2_1.0.8-6_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libseccomp2 amd64 2.6.0-2 [51.7 kB] Fetched 51.7 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpqevtk0v7/libseccomp2_2.6.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libxslt1.1 amd64 1.1.43-0.2 [155 kB] Fetched 155 kB in 0s (13.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmplfey59kw/libxslt1.1_1.1.43-0.2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-psutil amd64 7.0.0-2 [220 kB] Fetched 220 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp7qjdufnj/python3-psutil_7.0.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-tidyr amd64 1.3.1-1 [1163 kB] Fetched 1163 kB in 0s (79.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpy403hnb3/r-cran-tidyr_1.3.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libgav1-1 amd64 0.19.0-3+b1 [353 kB] Fetched 353 kB in 0s (33.3 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp55fwebn4/libgav1-1_0.19.0-3+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libgnutls30t64 amd64 3.8.10-2 [1484 kB] Fetched 1484 kB in 0s (90.9 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpwvm6zsbg/libgnutls30t64_3.8.10-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 fonts-mathjax all 2.7.9+dfsg-1 [2210 kB] Fetched 2210 kB in 0s (102 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpyv27pvac/fonts-mathjax_2.7.9+dfsg-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 liblzma5 amd64 5.8.1-1 [309 kB] Fetched 309 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpntt74peh/liblzma5_5.8.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libisl23 amd64 0.27-1 [659 kB] Fetched 659 kB in 0s (57.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmphahw514e/libisl23_0.27-1_amd64.deb' Downloading dependency 383 of 540: python3-colorama:amd64=0.4.6-4 Downloading dependency 384 of 540: libstdc++-14-dev:amd64=14.3.0-5 Downloading dependency 385 of 540: zlib1g-dev:amd64=1:1.3.dfsg+really1.3.1-1+b1 Downloading dependency 386 of 540: build-essential:amd64=12.12 Downloading dependency 387 of 540: libfontconfig1:amd64=2.15.0-2.3 Downloading dependency 388 of 540: libpython3-dev:amd64=3.13.7-1 Downloading dependency 389 of 540: libdebuginfod-common:amd64=0.192-4 Downloading dependency 390 of 540: python3-defusedxml:amd64=0.7.1-3 Downloading dependency 391 of 540: liblsan0:amd64=15.2.0-2 Downloading dependency 392 of 540: python-tinycss2-common:amd64=1.4.0-2 Downloading dependency 393 of 540: gettext:amd64=0.23.1-2+b1 Downloading dependency 394 of 540: python3-ipykernel:amd64=6.30.1-1 Downloading dependency 395 of 540: python3-pycparser:amd64=2.22-2 Downloading dependency 396 of 540: python3-notebook:amd64=6.4.13-5 Downloading dependency 397 of 540: libjansson4:amd64=2.14-2+b3 Downloading dependency 398 of 540: python3-sympy:amd64=1.14.0-2 Downloading dependency 399 of 540: libltdl7:amd64=2.5.4-4 Downloading dependency 400 of 540: libhwasan0:amd64=15.2.0-2 Downloading dependency 401 of 540: gdb:amd64=16.3-4 Downloading dependency 402 of 540: init-system-helpers:amd64=1.69 Downloading dependency 403 of 540: r-cran-statmod:amd64=1.5.0-1 Downloading dependency 404 of 540: bsdutils:amd64=1:2.41.1-1 Downloading dependency 405 of 540: python3-pandocfilters:amd64=1.5.1-1 Downloading dependency 406 of 540: python3-py:amd64=1.11.0-5 Downloading dependency 407 of 540: cpp:amd64=4:14.2.0-1 Downloading dependency 408 of 540: python3-kiwisolver:amd64=1.4.7-3+b1 Downloading dependency 409 of 540: libxt6t64:amd64=1:1.2.1-1.2+b2 Downloading dependency 410 of 540: r-cran-r6:amd64=2.6.1-1 Downloading dependency 411 of 540: python3-contourpy:amd64=1.3.1-2 Downloading dependency 412 of 540: libuuid1:amd64=2.41.1-1 Downloading dependency 413 of 540: libjodycode3t64:amd64=3.1.2-1 Downloading dependency 414 of 540: libmd0:amd64=1.1.0-2+b1 Downloading dependency 415 of 540: fonts-dejavu-core:amd64=2.37-8 Downloading dependency 416 of 540: libgfortran5:amd64=15.2.0-2 Downloading 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Downloading dependency 479 of 540: python3-joblib:amd64=1.4.2-5 Downloading dependency 480 of 540: python3-rpds-py:amd64=0.21.0-2+b1 Downloading dependency 481 of 540: r-cran-broom:amd64=1.0.7+dfsg-1 Downloading dependency 482 of 540: libblas3:amd64=3.12.1-6 Downloading dependency 483 of 540: binutils-x86-64-linux-gnu:amd64=2.45-4 Downloading dependency 484 of 540: libblkid1:amd64=2.41.1-1 Downloading dependency 485 of 540: libcrypt1:amd64=1:4.4.38-1 Downloading dependency 486 of 540: libjs-text-encoding:amd64=0.7.0-5 Downloading dependency 487 of 540: libfreetype6:amd64=2.13.3+dfsg-1 Downloading dependency 488 of 540: grep:amd64=3.11-4 Downloading dependency 489 of 540: jdupes:amd64=1.28.0-1 Downloading dependency 490 of 540: r-cran-boot:amd64=1.3-31-1 Downloading dependency 491 of 540: r-cran-pillar:amd64=1.10.1+dfsg-1 Downloading dependency 492 of 540: hostname:amd64=3.25 Downloading dependency 493 of 540: python3-iniconfig:amd64=1.1.1-2 Downloading dependency 494 of 540: 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libisl23:amd64=0.27-1 Downloading dependency 511 of 540: python3-tzlocal:amd64=5.3.1-1Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-tzlocal all 5.3.1-1 [24.2 kB] Fetched 24.2 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmptua9vwp2/python3-tzlocal_5.3.1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250904T023413Z sid/main amd64 gcc-15-base amd64 15.2.0-2 [52.3 kB] Fetched 52.3 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpxguwzyc4/gcc-15-base_15.2.0-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 bsdextrautils amd64 2.41.1-1 [94.7 kB] Fetched 94.7 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmps9_xn82w/bsdextrautils_2.41.1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libqhull-r8.0 amd64 2020.2-6+b2 [248 kB] Fetched 248 kB in 0s (24.2 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpxg9ecctg/libqhull-r8.0_2020.2-6+b2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-inflect all 7.3.1-2 [32.4 kB] Fetched 32.4 kB in 0s (2804 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpp4ep_jr_/python3-inflect_7.3.1-2_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-mpmath all 1.3.0-1 [419 kB] Fetched 419 kB in 0s (41.5 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpab_v5q3w/python3-mpmath_1.3.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-nbconvert all 7.16.6-1 [160 kB] Fetched 160 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpdzmkmlwt/python3-nbconvert_7.16.6-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libdebuginfod1t64 amd64 0.192-4 [32.4 kB] Fetched 32.4 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp_duaau3_/libdebuginfod1t64_0.192-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-cffi-backend amd64 2.0.0~b1-1 [94.4 kB] Fetched 94.4 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpx0zes6na/python3-cffi-backend_2.0.0~b1-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libxcb1 amd64 1.17.0-2+b1 [144 kB] Fetched 144 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp01uw5k4o/libxcb1_1.17.0-2+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libsm6 amd64 2:1.2.6-1 [37.3 kB] Fetched 37.3 kB in 0s (0 B/s) dpkg-name: info: moved 'libsm6_2%3a1.2.6-1_amd64.deb' to '/srv/rebuilderd/tmp/tmpfddja56k/libsm6_1.2.6-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-pyproject-hooks all 1.2.0-1 [11.7 kB] Fetched 11.7 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpyqb_9yik/python3-pyproject-hooks_1.2.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libfftw3-double3 amd64 3.3.10-2+b1 [781 kB] Fetched 781 kB in 0s (60.6 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpbrf7xswj/libfftw3-double3_3.3.10-2+b1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 patch amd64 2.8-2 [134 kB] Fetched 134 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpf8f57p2f/patch_2.8-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpam-modules amd64 1.7.0-5 [179 kB] Fetched 179 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpyxr6zfss/libpam-modules_1.7.0-5_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjs-jquery-ui all 1.13.2+dfsg-1 [250 kB] Fetched 250 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpmfh7vnzh/libjs-jquery-ui_1.13.2+dfsg-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-pytz all 2025.2-3 [152 kB] Fetched 152 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmptzlle14z/python3-pytz_2025.2-3_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libbsd0 amd64 0.12.2-2 [131 kB] Fetched 131 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpbfa6cggq/libbsd0_0.12.2-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-lattice amd64 0.22-7-1 [1418 kB] Fetched 1418 kB in 0s (90.4 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpss651o22/r-cran-lattice_0.22-7-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-numpy-dev amd64 1:2.2.4+ds-1 [139 kB] Fetched 139 kB in 0s (0 B/s) dpkg-name: info: moved 'python3-numpy-dev_1%3a2.2.4+ds-1_amd64.deb' to '/srv/rebuilderd/tmp/tmp5dcs5mev/python3-numpy-dev_2.2.4+ds-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libncursesw6 amd64 6.5+20250216-2 [135 kB] Fetched 135 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp3054_0r7/libncursesw6_6.5+20250216-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libjpeg62-turbo amd64 1:2.1.5-4 [168 kB] Fetched 168 kB in 0s (0 B/s) dpkg-name: info: moved 'libjpeg62-turbo_1%3a2.1.5-4_amd64.deb' to '/srv/rebuilderd/tmp/tmpmdtk8nzb/libjpeg62-turbo_2.1.5-4_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python-babel-localedata all 2.17.0-1 [6050 kB] Fetched 6050 kB in 0s (147 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmphdq0song/python-babel-localedata_2.17.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libtinfo6 amd64 6.5+20250216-2 [348 kB] Fetched 348 kB in 0s (29.5 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpe9w3xeu3/libtinfo6_6.5+20250216-2_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 r-cran-rdpack all 2.6.3-1 [638 kB] Fetched 638 kB in 2s (382 kB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpnb3skxsd/r-cran-rdpack_2.6.3-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-snowballstemmer all 3.0.1-1 [63.5 kB] Fetched 63.5 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmppqhqc4b1/python3-snowballstemmer_3.0.1-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-pluggy all 1.6.0-1 [27.1 kB] Fetched 27.1 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp6z0los_3/python3-pluggy_1.6.0-1_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 python3-webencodings all 0.5.1-5 [11.1 kB] Fetched 11.1 kB in 0s (0 B/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpmx2f3tnf/python3-webencodings_0.5.1-5_all.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 libpython3.13-minimal amd64 3.13.7-1 [864 kB] Fetched 864 kB in 0s (69.1 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmp6bqlk78g/libpython3.13-minimal_3.13.7-1_amd64.deb' Get:1 http://snapshot.debian.org/archive/debian/20250828T083238Z sid/main amd64 perl-modules-5.40 all 5.40.1-6 [3019 kB] Fetched 3019 kB in 0s (124 MB/s) dpkg-name: warning: skipping '/srv/rebuilderd/tmp/tmpdg_6z8dw/perl-modules-5.40_5.40.1-6_all.deb' dpkg-buildpackage: info: source package debootsnap-dummy dpkg-buildpackage: info: source version 1.0 dpkg-buildpackage: info: source distribution unstable dpkg-buildpackage: info: source changed by Equivs Dummy Package Generator dpkg-buildpackage: info: host architecture amd64 dpkg-source --before-build . debian/rules clean dh clean dh_clean debian/rules binary dh binary dh_update_autotools_config dh_autoreconf create-stamp debian/debhelper-build-stamp dh_prep dh_auto_install --destdir=debian/debootsnap-dummy/ dh_install dh_installdocs dh_installchangelogs dh_perl dh_link dh_strip_nondeterminism dh_compress dh_fixperms dh_missing dh_installdeb dh_gencontrol dh_md5sums dh_builddeb dpkg-deb: building package 'debootsnap-dummy' in '../debootsnap-dummy_1.0_all.deb'. dpkg-genbuildinfo --build=binary -O../debootsnap-dummy_1.0_amd64.buildinfo dpkg-genchanges --build=binary -O../debootsnap-dummy_1.0_amd64.changes dpkg-genchanges: info: binary-only upload (no source code included) dpkg-source --after-build . dpkg-buildpackage: info: binary-only upload (no source included) The package has been created. Attention, the package has been created in the /srv/rebuilderd/tmp/tmpas88vwnx/cache directory, not in ".." as indicated by the message above! I: automatically chosen mode: unshare I: chroot architecture amd64 is equal to the host's architecture I: using /srv/rebuilderd/tmp/mmdebstrap.Hrzbl74ZXf as tempdir I: running --setup-hook directly: /usr/share/mmdebstrap/hooks/maybe-merged-usr/setup00.sh /srv/rebuilderd/tmp/mmdebstrap.Hrzbl74ZXf 127.0.0.1 - - [02/Oct/2025 08:36:05] code 404, message File not found 127.0.0.1 - - [02/Oct/2025 08:36:05] "GET /./InRelease HTTP/1.1" 404 - Ign:1 http://localhost:45719 ./ InRelease 127.0.0.1 - - [02/Oct/2025 08:36:05] "GET /./Release HTTP/1.1" 200 - Get:2 http://localhost:45719 ./ Release [462 B] 127.0.0.1 - - [02/Oct/2025 08:36:05] code 404, message File not found 127.0.0.1 - - [02/Oct/2025 08:36:05] "GET /./Release.gpg HTTP/1.1" 404 - Ign:3 http://localhost:45719 ./ Release.gpg 127.0.0.1 - - [02/Oct/2025 08:36:05] "GET /./Packages HTTP/1.1" 200 - Get:4 http://localhost:45719 ./ Packages [675 kB] Fetched 676 kB in 0s (20.9 MB/s) Reading package lists... usr-is-merged found but not real -- not running merged-usr setup hook I: skipping apt-get update because it was already run I: downloading packages with apt... 127.0.0.1 - - [02/Oct/2025 08:36:05] "GET /./gcc-15-base_15.2.0-2_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:05] "GET /./libc6_2.41-12_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:05] "GET /./libgcc-s1_15.2.0-2_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:05] "GET /./mawk_1.3.4.20250131-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:05] "GET /./base-files_14_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:05] "GET /./libtinfo6_6.5%2b20250216-2_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:05] "GET /./debianutils_5.23.2_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:05] "GET /./bash_5.2.37-2%2bb5_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:05] "GET /./libcap2_2.75-10%2bb1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:05] "GET /./libsystemd0_258%7erc3-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:05] "GET /./bsdutils_2.41.1-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:05] "GET /./libacl1_2.3.2-2%2bb1_amd64.deb HTTP/1.1" 200 - 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127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libbz2-1.0_1.0.8-6_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./liblzma5_5.8.1-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libmd0_1.1.0-2%2bb1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./tar_1.35%2bdfsg-3.1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./dpkg_1.22.21_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./findutils_4.10.0-3_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./grep_3.11-4_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./gzip_1.13-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./hostname_3.25_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./ncurses-bin_6.5%2b20250216-2_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libcrypt1_4.4.38-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./perl-base_5.40.1-6_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./sed_4.9-2_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libaudit-common_4.0.5-1_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libcap-ng0_0.8.5-4%2bb1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libaudit1_4.0.5-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libdb5.3t64_5.3.28%2bdfsg2-9_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./debconf_1.5.91_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libpam0g_1.7.0-5_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libpam-modules-bin_1.7.0-5_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libpam-modules_1.7.0-5_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libpam-runtime_1.7.0-5_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libblkid1_2.41.1-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libsqlite3-0_3.46.1-7_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./liblastlog2-2_2.41.1-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libmount1_2.41.1-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libsmartcols1_2.41.1-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libudev1_258%7erc3-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libuuid1_2.41.1-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./util-linux_2.41.1-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libdebconfclient0_0.280_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./base-passwd_3.6.7_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./init-system-helpers_1.69_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./libc-bin_2.41-12_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./ncurses-base_6.5%2b20250216-2_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:06] "GET /./sysvinit-utils_3.14-4_amd64.deb HTTP/1.1" 200 - I: extracting archives... I: running --extract-hook directly: /usr/share/mmdebstrap/hooks/maybe-merged-usr/extract00.sh /srv/rebuilderd/tmp/mmdebstrap.Hrzbl74ZXf 127.0.0.1 - - [02/Oct/2025 08:36:07] code 404, message File not found 127.0.0.1 - - [02/Oct/2025 08:36:07] "GET /./InRelease HTTP/1.1" 404 - Ign:1 http://localhost:45719 ./ InRelease 127.0.0.1 - - [02/Oct/2025 08:36:07] "GET /./Release HTTP/1.1" 304 - Hit:2 http://localhost:45719 ./ Release 127.0.0.1 - - [02/Oct/2025 08:36:07] code 404, message File not found 127.0.0.1 - - [02/Oct/2025 08:36:07] "GET /./Release.gpg HTTP/1.1" 404 - Ign:3 http://localhost:45719 ./ Release.gpg Reading package lists... usr-is-merged found but not real -- not running merged-usr extract hook I: installing essential packages... I: running --essential-hook directly: /usr/share/mmdebstrap/hooks/maybe-merged-usr/essential00.sh /srv/rebuilderd/tmp/mmdebstrap.Hrzbl74ZXf usr-is-merged was not installed in a previous hook -- not running merged-usr essential hook I: installing remaining packages inside the chroot... 127.0.0.1 - - [02/Oct/2025 08:36:12] "GET /./libtext-charwidth-perl_0.04-11%2bb4_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:12] "GET /./libtext-wrapi18n-perl_0.06-10_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:12] "GET /./libncursesw6_6.5%2b20250216-2_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:12] "GET /./libproc2-0_4.0.4-9_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:12] "GET /./procps_4.0.4-9_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:12] "GET /./sensible-utils_0.0.26_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:12] "GET /./ucf_3.0052_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:12] "GET /./libdebuginfod-common_0.192-4_all.deb HTTP/1.1" 200 - 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127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./python3-matplotlib_3.10.1%2bdfsg1-4_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./libjs-moment_2.29.4%2bds-1_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./libltdl7_2.5.4-4_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./libglpk40_5.0-2_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./fonts-font-awesome_5.0.10%2breally4.7.0%7edfsg-4.1_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./python3-pickleshare_0.7.5-5_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./python3-seaborn_0.13.2-5_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./libjs-backbone_1.4.1%7edfsg%2b%7e1.4.15-3_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./r-cran-lmtest_0.9.40-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./r-cran-vcd_1.4-13-1_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./libdsdp-5.8t64_5.8-10.1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./python3-prometheus-client_0.21.1%2bds1-1_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./libpython3-dev_3.13.7-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./libpython3-all-dev_3.13.7-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./python3-colorama_0.4.6-4_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./python3-ipykernel_6.30.1-1_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./libjs-jed_1.1.1-4_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./libjs-text-encoding_0.7.0-5_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./python3-notebook_6.4.13-5_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./r-cran-statmod_1.5.0-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./libjodycode3t64_3.1.2-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./libumfpack6_7.11.0%2bdfsg-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./r-cran-boot_1.3-31-1_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./r-cran-lme4_1.1-37-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./libfftw3-double3_3.3.10-2%2bb1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./python3-cvxopt_1.3.0%2bdfsg-1%2bb9_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./python3-numpydoc_1.9.0-1_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:21] "GET /./pandoc_3.1.11.1%2bds-3_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:22] "GET /./python3-dev_3.13.7-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:22] "GET /./python3-all-dev_3.13.7-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:22] "GET /./python-pandas-doc_2.2.3%2bdfsg-9_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:22] "GET /./python3-joblib_1.4.2-5_all.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:22] "GET /./jdupes_1.28.0-1_amd64.deb HTTP/1.1" 200 - 127.0.0.1 - - [02/Oct/2025 08:36:22] "GET /./debootsnap-dummy_1.0_all.deb HTTP/1.1" 200 - I: running --customize-hook directly: /srv/rebuilderd/tmp/tmpas88vwnx/apt_install.sh /srv/rebuilderd/tmp/mmdebstrap.Hrzbl74ZXf Reading package lists... Building dependency tree... Reading state information... libjs-requirejs-text is already the newest version (2.0.12-1.1). libjs-requirejs-text set to manually installed. libcurl3t64-gnutls is already the newest version (8.16.0~rc2-1). libcurl3t64-gnutls set to manually installed. libk5crypto3 is already the newest version (1.21.3-5). libk5crypto3 set to manually installed. python3-referencing is already the newest version (0.36.2-1). python3-referencing set to manually installed. python3-rpy2 is already the newest version (3.5.17-2). python3-rpy2 set to manually installed. fontconfig-config is already the newest version (2.15.0-2.3). fontconfig-config set to manually installed. python3-zmq is already the newest version (26.4.0-1). python3-zmq set to manually installed. python3-nbsphinx is already the newest version (0.9.5+ds-1). python3-nbsphinx set to manually installed. dwz is already the newest version (0.15-1+b1). dwz set to manually installed. libfile-stripnondeterminism-perl is already the newest version (1.14.2-1). libfile-stripnondeterminism-perl set to manually installed. libsodium23 is already the newest version (1.0.18-1+b2). libsodium23 set to manually installed. libudev1 is already the newest version (258~rc3-1). r-cran-littler is already the newest version (0.3.21-1). r-cran-littler set to manually installed. libsvtav1enc2 is already the newest version (2.3.0+dfsg-1). libsvtav1enc2 set to manually installed. binutils-common is already the newest version (2.45-4). binutils-common set to manually installed. libpipeline1 is already the newest version (1.5.8-1). libpipeline1 set to manually installed. python3-send2trash is already the newest version (1.8.3-1). python3-send2trash set to manually installed. libtool is already the newest version (2.5.4-4). libtool set to manually installed. python3-nest-asyncio is already the newest version (1.5.4-1). python3-nest-asyncio set to manually installed. r-cran-reformulas is already the newest version (0.4.1-1). r-cran-reformulas set to manually installed. r-cran-sp is already the newest version (1:2.2-0+dfsg-1). r-cran-sp set to manually installed. libipt2 is already the newest version (2.1.2-1). libipt2 set to manually installed. g++-14-x86-64-linux-gnu is already the newest version (14.3.0-5). g++-14-x86-64-linux-gnu set to manually installed. python3-tornado is already the newest version (6.4.2-3). python3-tornado set to manually installed. libnuma1 is already the newest version (2.0.19-1). libnuma1 set to manually installed. r-cran-colorspace is already the newest version (2.1-1+dfsg-1). r-cran-colorspace set to manually installed. python3-babel is already the newest version (2.17.0-1). python3-babel set to manually installed. python3-typing-extensions is already the newest version (4.15.0-1). python3-typing-extensions set to manually installed. r-cran-rcppeigen is already the newest version (0.3.4.0.2-1). r-cran-rcppeigen set to manually installed. dh-python is already the newest version (6.20250414). dh-python set to manually installed. python3 is already the newest version (3.13.7-1). python3 set to manually installed. python3-jaraco.text is already the newest version (4.0.0-1). python3-jaraco.text set to manually installed. python3-jupyter-client is already the newest version (8.6.3-2). python3-jupyter-client set to manually installed. python3-jsonschema is already the newest version (4.19.2-6). python3-jsonschema set to manually installed. libjson-perl is already the newest version (4.10000-1). libjson-perl set to manually installed. python3-nbformat is already the newest version (5.9.1-1). python3-nbformat set to manually installed. python3-doc is already the newest version (3.13.7-1). python3-doc set to manually installed. libpaper2 is already the newest version (2.2.5-0.3+b2). libpaper2 set to manually installed. sensible-utils is already the newest version (0.0.26). sensible-utils set to manually installed. libpixman-1-0 is already the newest version (0.44.0-3). libpixman-1-0 set to manually installed. python3-executing is already the newest version (2.2.0-0.3). python3-executing set to manually installed. g++ is already the newest version (4:14.2.0-1). g++ set to manually installed. unicode-data is already the newest version (15.1.0-1). unicode-data set to manually installed. libsframe2 is already the newest version (2.45-4). libsframe2 set to manually installed. r-cran-nlme is already the newest version (3.1.168-1). r-cran-nlme set to manually installed. python3-zipp is already the newest version (3.21.0-1). python3-zipp set to manually installed. libkrb5-3 is already the newest version (1.21.3-5). libkrb5-3 set to manually installed. perl-base is already the newest version (5.40.1-6). libgraphite2-3 is already the newest version (1.3.14-3). libgraphite2-3 set to manually installed. r-cran-deoptimr is already the newest version (1.1-4-1). r-cran-deoptimr set to manually installed. coreutils is already the newest version (9.7-3). r-cran-robustbase is already the newest version (0.99-4-1-1). r-cran-robustbase set to manually installed. python3-idna is already the newest version (3.10-1). python3-idna set to manually installed. r-cran-minqa is already the newest version (1.2.8-1). r-cran-minqa set to manually installed. python3-setuptools-scm is already the newest version (8.2.1-2). python3-setuptools-scm set to manually installed. r-cran-generics is already the newest version (0.1.3-1). r-cran-generics set to manually installed. libcurl4t64 is already the newest version (8.16.0~rc2-1). libcurl4t64 set to manually installed. libjs-codemirror is already the newest version (5.65.20+~cs5.83.25-1). libjs-codemirror set to manually installed. python3-pandas is already the newest version (2.2.3+dfsg-9). python3-pandas set to manually installed. libidn2-0 is already the newest version (2.3.8-4). libidn2-0 set to manually installed. liblerc4 is already the newest version (4.0.0+ds-5). liblerc4 set to manually installed. libpgm-5.3-0t64 is already the newest version (5.3.128~dfsg-2.1+b1). libpgm-5.3-0t64 set to manually installed. python3-stack-data is already the newest version (0.6.3-1). python3-stack-data set to manually installed. libc6-dev is already the newest version (2.41-12). libc6-dev set to manually installed. python3-jinja2 is already the newest version (3.1.6-1). python3-jinja2 set to manually installed. python3.13-dev is already the newest version (3.13.7-1). python3.13-dev set to manually installed. libgcc-14-dev is already the newest version (14.3.0-5). libgcc-14-dev set to manually installed. libxrender1 is already the newest version (1:0.9.12-1). libxrender1 set to manually installed. file is already the newest version (1:5.46-5). file set to manually installed. libnghttp2-14 is already the newest version (1.64.0-1.1+b1). libnghttp2-14 set to manually installed. python3-fs is already the newest version (2.4.16-7). python3-fs set to manually installed. python3-mistune is already the newest version (3.1.3-1). python3-mistune set to manually installed. libjs-es6-promise is already the newest version (4.2.8-12). libjs-es6-promise set to manually installed. python3-traitlets is already the newest version (5.14.3+really5.14.3-1). python3-traitlets set to manually installed. r-cran-matrix is already the newest version (1.7-4-1). r-cran-matrix set to manually installed. libgprofng0 is already the newest version (2.45-4). libgprofng0 set to manually installed. python3-sphinx is already the newest version (8.2.3-2). python3-sphinx set to manually installed. libwebpmux3 is already the newest version (1.5.0-0.1). libwebpmux3 set to manually installed. python3-certifi is already the newest version (2025.1.31+ds-1). python3-certifi set to manually installed. media-types is already the newest version (13.0.0). media-types set to manually installed. libpython3.13-dev is already the newest version (3.13.7-1). libpython3.13-dev set to manually installed. tar is already the newest version (1.35+dfsg-3.1). r-cran-dplyr is already the newest version (1.1.4-4). r-cran-dplyr set to manually installed. readline-common is already the newest version (8.3-2). readline-common set to manually installed. xdg-utils is already the newest version (1.2.1-2). xdg-utils set to manually installed. libdpkg-perl is already the newest version (1.22.21). libdpkg-perl set to manually installed. libbinutils is already the newest version (2.45-4). libbinutils set to manually installed. libcom-err2 is already the newest version (1.47.2-3+b3). libcom-err2 set to manually installed. python3-yapf is already the newest version (0.43.0-1). python3-yapf set to manually installed. cython3 is already the newest version (3.0.11+dfsg-2+b1). cython3 set to manually installed. python3-pexpect is already the newest version (4.9-3). python3-pexpect set to manually installed. libmpfr6 is already the newest version (4.2.2-1). libmpfr6 set to manually installed. libmpc3 is already the newest version (1.3.1-1+b3). libmpc3 set to manually installed. python3.13-tk is already the newest version (3.13.7-1). python3.13-tk set to manually installed. fonts-glyphicons-halflings is already the newest version (1.009~3.4.1+dfsg-6). fonts-glyphicons-halflings set to manually installed. libfribidi0 is already the newest version (1.0.16-1). libfribidi0 set to manually installed. zlib1g is already the newest version (1:1.3.dfsg+really1.3.1-1+b1). python3-argon2-cffi-bindings is already the newest version (25.1.0-2). python3-argon2-cffi-bindings set to manually installed. libngtcp2-crypto-gnutls8 is already the newest version (1.11.0-1). libngtcp2-crypto-gnutls8 set to manually installed. python3-numpy is already the newest version (1:2.2.4+ds-1). python3-numpy set to manually installed. libgmp10 is already the newest version (2:6.3.0+dfsg-4). libc6 is already the newest version (2.41-12). python3-prompt-toolkit is already the newest version (3.0.52-1). python3-prompt-toolkit set to manually installed. libacl1 is already the newest version (2.3.2-2+b1). r-cran-stringr is already the newest version (1.5.1-1). r-cran-stringr set to manually installed. autoconf is already the newest version (2.72-3.1). autoconf set to manually installed. r-cran-pkgkitten is already the newest version (0.2.4-1). r-cran-pkgkitten set to manually installed. python3-pytest-forked is already the newest version (1.6.0-3). python3-pytest-forked set to manually installed. python3-ipython-genutils is already the newest version (0.2.0-7). python3-ipython-genutils set to manually installed. python3-matplotlib-inline is already the newest version (0.1.7-1). python3-matplotlib-inline set to manually installed. python3-docutils is already the newest version (0.21.2+dfsg-2). python3-docutils set to manually installed. libubsan1 is already the newest version (15.2.0-2). libubsan1 set to manually installed. libamd3 is already the newest version (1:7.11.0+dfsg-1). libamd3 set to manually installed. libsasl2-2 is already the newest version (2.1.28+dfsg1-9). libsasl2-2 set to manually installed. libstdc++6 is already the newest version (15.2.0-2). libstdc++6 set to manually installed. python3-ipython is already the newest version (8.35.0-1). python3-ipython set to manually installed. libcrypt-dev is already the newest version (1:4.4.38-1). libcrypt-dev set to manually installed. libjs-jquery-typeahead is already the newest version (2.11.0+dfsg1-3). libjs-jquery-typeahead set to manually installed. libpsl5t64 is already the newest version (0.21.2-1.1+b1). libpsl5t64 set to manually installed. python3-cycler is already the newest version (0.12.1-2). python3-cycler set to manually installed. sed is already the newest version (4.9-2). base-files is already the newest version (14). liblz4-1 is already the newest version (1.10.0-4). liblz4-1 set to manually installed. libexpat1-dev is already the newest version (2.7.1-2). libexpat1-dev set to manually installed. libjbig0 is already the newest version (2.1-6.1+b2). libjbig0 set to manually installed. sphinx-common is already the newest version (8.2.3-2). sphinx-common set to manually installed. ncurses-bin is already the newest version (6.5+20250216-2). python3-ptyprocess is already the newest version (0.7.0-6). python3-ptyprocess set to manually installed. libldap2 is already the newest version (2.6.10+dfsg-1). libldap2 set to manually installed. libxcb-render0 is already the newest version (1.17.0-2+b1). libxcb-render0 set to manually installed. libpython3.13 is already the newest version (3.13.7-1). libpython3.13 set to manually installed. libnorm1t64 is already the newest version (1.5.9+dfsg-3.1+b2). libnorm1t64 set to manually installed. libx11-data is already the newest version (2:1.8.12-1). libx11-data set to manually installed. libgdbm6t64 is already the newest version (1.26-1). libgdbm6t64 set to manually installed. python3-nbclient is already the newest version (0.8.0-3). python3-nbclient set to manually installed. libjs-marked is already the newest version (4.2.3+ds+~4.0.7-4). libjs-marked set to manually installed. python3-jedi is already the newest version (0.19.1+ds1-1). python3-jedi set to manually installed. python3-scipy is already the newest version (1.15.3-1). python3-scipy set to manually installed. libasan8 is already the newest version (15.2.0-2). libasan8 set to manually installed. python3-patsy is already the newest version (1.0.1-1). python3-patsy set to manually installed. intltool-debian is already the newest version (0.35.0+20060710.6). intltool-debian set to manually installed. python3-coverage is already the newest version (7.8.2+dfsg1-1). python3-coverage set to manually installed. python3-setuptools is already the newest version (78.1.1-0.1). python3-setuptools set to manually installed. libuchardet0 is already the newest version (0.0.8-1+b2). libuchardet0 set to manually installed. python3-pygments is already the newest version (2.18.0+dfsg-2). python3-pygments set to manually installed. libpango-1.0-0 is already the newest version (1.56.3-1). libpango-1.0-0 set to manually installed. python3-jsonschema-specifications is already the newest version (2023.12.1-2). python3-jsonschema-specifications set to manually installed. gcc-14 is already the newest version (14.3.0-5). gcc-14 set to manually installed. libdeflate0 is already the newest version (1.23-2). libdeflate0 set to manually installed. debhelper is already the newest version (13.26). debhelper set to manually installed. cpp-14 is already the newest version (14.3.0-5). cpp-14 set to manually installed. dpkg-dev is already the newest version (1.22.21). dpkg-dev set to manually installed. r-cran-geepack is already the newest version (1.3.12-1). r-cran-geepack set to manually installed. r-cran-withr is already the newest version (3.0.2+dfsg-1). r-cran-withr set to manually installed. linux-libc-dev is already the newest version (6.16.3-1). linux-libc-dev set to manually installed. python3-brotli is already the newest version (1.1.0-2+b7). python3-brotli set to manually installed. python3-tinycss2 is already the newest version (1.4.0-2). python3-tinycss2 set to manually installed. libproc2-0 is already the newest version (2:4.0.4-9). libproc2-0 set to manually installed. libargon2-1 is already the newest version (0~20190702+dfsg-5). libargon2-1 set to manually installed. libpangoft2-1.0-0 is already the newest version (1.56.3-1). libpangoft2-1.0-0 set to manually installed. libngtcp2-16 is already the newest version (1.11.0-1). libngtcp2-16 set to manually installed. libnlopt0 is already the newest version (2.7.1-6+b4). libnlopt0 set to manually installed. libctf-nobfd0 is already the newest version (2.45-4). libctf-nobfd0 set to manually installed. python-numpy-doc is already the newest version (1:2.2.4+ds-1). python-numpy-doc set to manually installed. python3-build is already the newest version (1.2.2-4). python3-build set to manually installed. dh-autoreconf is already the newest version (20). dh-autoreconf set to manually installed. r-cran-nloptr is already the newest version (2.2.1-2). r-cran-nloptr set to manually installed. bash is already the newest version (5.2.37-2+b5). libatomic1 is already the newest version (15.2.0-2). libatomic1 set to manually installed. python3-asttokens is already the newest version (3.0.0-2). python3-asttokens set to manually installed. libtiff6 is already the newest version (4.7.0-4). libtiff6 set to manually installed. libjs-bootstrap-tour is already the newest version (0.12.0+dfsg-5). libjs-bootstrap-tour set to manually installed. debianutils is already the newest version (5.23.2). python3-jupyterlab-pygments is already the newest version (0.2.2-3). python3-jupyterlab-pygments set to manually installed. libcholmod5 is already the newest version (1:7.11.0+dfsg-1). libcholmod5 set to manually installed. libicu76 is already the newest version (76.1-4). libicu76 set to manually installed. libgpg-error0 is already the newest version (1.55-2). libgpg-error0 set to manually installed. libctf0 is already the newest version (2.45-4). libctf0 set to manually installed. r-cran-tibble is already the newest version (3.2.1+dfsg-3). r-cran-tibble set to manually installed. cpp-x86-64-linux-gnu is already the newest version (4:14.2.0-1). cpp-x86-64-linux-gnu set to manually installed. libselinux1 is already the newest version (3.8.1-1). liblua5.4-0 is already the newest version (5.4.8-1). liblua5.4-0 set to manually installed. libxxhash0 is already the newest version (0.8.3-2). libxxhash0 set to manually installed. libxml2-16 is already the newest version (2.14.5+dfsg-0.2). libxml2-16 set to manually installed. libpam-modules-bin is already the newest version (1.7.0-5). libthai0 is already the newest version (0.1.29-2+b1). libthai0 set to manually installed. python3-platformdirs is already the newest version (4.3.7-1). python3-platformdirs set to manually installed. python3-chardet is already the newest version (5.2.0+dfsg-2). python3-chardet set to manually installed. libopenjp2-7 is already the newest version (2.5.3-2.1). libopenjp2-7 set to manually installed. python-scipy-doc is already the newest version (1.15.3-1). python-scipy-doc set to manually installed. python3-pil.imagetk is already the newest version (11.3.0-1). python3-pil.imagetk set to manually installed. libgssapi-krb5-2 is already the newest version (1.21.3-5). libgssapi-krb5-2 set to manually installed. python3-parso is already the newest version (0.8.4-1). python3-parso set to manually installed. sysvinit-utils is already the newest version (3.14-4). r-cran-cli is already the newest version (3.6.4-1). r-cran-cli set to manually installed. unzip is already the newest version (6.0-29). unzip set to manually installed. python3-jupyter-core is already the newest version (5.7.2-5). python3-jupyter-core set to manually installed. autotools-dev is already the newest version (20240727.1). autotools-dev set to manually installed. libpam0g is already the newest version (1.7.0-5). python-matplotlib-data is already the newest version (3.10.1+dfsg1-4). python-matplotlib-data set to manually installed. r-cran-stringi is already the newest version (1.8.4-1+b1). r-cran-stringi set to manually installed. procps is already the newest version (2:4.0.4-9). procps set to manually installed. librav1e0.7 is already the newest version (0.7.1-9+b2). librav1e0.7 set to manually installed. libjs-sphinxdoc is already the newest version (8.2.3-2). libjs-sphinxdoc set to manually installed. libgcrypt20 is already the newest version (1.11.2-2). libgcrypt20 set to manually installed. r-cran-purrr is already the newest version (1.0.4-1). r-cran-purrr set to manually installed. python3-imagesize is already the newest version (1.4.1-1). python3-imagesize set to manually installed. sgml-base is already the newest version (1.31+nmu1). sgml-base set to manually installed. python3-debugpy is already the newest version (1.8.12+ds-1). python3-debugpy set to manually installed. python3.13-minimal is already the newest version (3.13.7-1). python3.13-minimal set to manually installed. libsource-highlight-common is already the newest version (3.1.9-4.3). libsource-highlight-common set to manually installed. debconf is already the newest version (1.5.91). python3-jaraco.functools is already the newest version (4.1.0-1). python3-jaraco.functools set to manually installed. python3-more-itertools is already the newest version (10.7.0-1). python3-more-itertools set to manually installed. python3-comm is already the newest version (0.2.1-1). python3-comm set to manually installed. r-cran-zoo is already the newest version (1.8-14-1). r-cran-zoo set to manually installed. g++-14 is already the newest version (14.3.0-5). g++-14 set to manually installed. python3-roman-numerals is already the newest version (3.1.0-2). python3-roman-numerals set to manually installed. fonts-open-sans is already the newest version (1.11-2). fonts-open-sans set to manually installed. python3-bleach is already the newest version (6.2.0-1). python3-bleach set to manually installed. libdb5.3t64 is already the newest version (5.3.28+dfsg2-9). g++-x86-64-linux-gnu is already the newest version (4:14.2.0-1). g++-x86-64-linux-gnu set to manually installed. libabsl20240722 is already the newest version (20240722.0-4). libabsl20240722 set to manually installed. man-db is already the newest version (2.13.1-1). man-db set to manually installed. libsuitesparseconfig7 is already the newest version (1:7.11.0+dfsg-1). libsuitesparseconfig7 set to manually installed. libexpat1 is already the newest version (2.7.1-2). libexpat1 set to manually installed. python3-argon2 is already the newest version (25.1.0-2). python3-argon2 set to manually installed. libgcc-s1 is already the newest version (15.2.0-2). libsasl2-modules-db is already the newest version (2.1.28+dfsg1-9). libsasl2-modules-db set to manually installed. libimagequant0 is already the newest version (4.4.0-3). libimagequant0 set to manually installed. libsqlite3-0 is already the newest version (3.46.1-7). python3-requests is already the newest version (2.32.5+dfsg-1). python3-requests set to manually installed. libxau6 is already the newest version (1:1.0.11-1). libxau6 set to manually installed. pybuild-plugin-pyproject is already the newest version (6.20250414). pybuild-plugin-pyproject set to manually installed. python3-html5lib is already the newest version (1.2-2). python3-html5lib set to manually installed. r-cran-utf8 is already the newest version (1.2.4-1). r-cran-utf8 set to manually installed. libarchive-zip-perl is already the newest version (1.68-1). libarchive-zip-perl set to manually installed. libtext-wrapi18n-perl is already the newest version (0.06-10). libtext-wrapi18n-perl set to manually installed. libjs-requirejs is already the newest version (2.3.7+ds+~2.1.37-1). libjs-requirejs set to manually installed. po-debconf is already the newest version (1.0.21+nmu1). po-debconf set to manually installed. python3-markupsafe is already the newest version (2.1.5-1+b3). python3-markupsafe set to manually installed. mawk is already the newest version (1.3.4.20250131-1). libhogweed6t64 is already the newest version (3.10.1-1). libhogweed6t64 set to manually installed. python3-decorator is already the newest version (5.2.1-2). python3-decorator set to manually installed. libice6 is already the newest version (2:1.1.1-1). libice6 set to manually installed. libharfbuzz0b is already the newest version (10.2.0-1+b1). libharfbuzz0b set to manually installed. libbrotli1 is already the newest version (1.1.0-2+b7). libbrotli1 set to manually installed. python3-urllib3 is already the newest version (2.5.0-1). python3-urllib3 set to manually installed. libsharpyuv0 is already the newest version (1.5.0-0.1). libsharpyuv0 set to manually installed. libsmartcols1 is already the newest version (2.41.1-1). libtirpc-common is already the newest version (1.3.6+ds-1). libtirpc-common set to manually installed. libpng16-16t64 is already the newest version (1.6.50-1). libpng16-16t64 set to manually installed. libjson-c5 is already the newest version (0.18+ds-1). libjson-c5 set to manually installed. libjs-jquery is already the newest version (3.7.1+dfsg+~3.5.33-1). libjs-jquery set to manually installed. libdatrie1 is already the newest version (0.2.13-4). libdatrie1 set to manually installed. libsystemd0 is already the newest version (258~rc3-1). libgsl28 is already the newest version (2.8+dfsg-5). libgsl28 set to manually installed. libnettle8t64 is already the newest version (3.10.1-1). libnettle8t64 set to manually installed. groff-base is already the newest version (1.23.0-9). groff-base set to manually installed. libraqm0 is already the newest version (0.10.3-1). libraqm0 set to manually installed. python3-pil is already the newest version (11.3.0-1). python3-pil set to manually installed. python3-ufolib2 is already the newest version (0.17.1+dfsg1-1). python3-ufolib2 set to manually installed. python3-simplegeneric is already the newest version (0.8.1-5). python3-simplegeneric set to manually installed. libffi8 is already the newest version (3.4.8-2). libffi8 set to manually installed. blt is already the newest version (2.5.3+dfsg-8). blt set to manually installed. cpp-14-x86-64-linux-gnu is already the newest version (14.3.0-5). cpp-14-x86-64-linux-gnu set to manually installed. libpaper-utils is already the newest version (2.2.5-0.3+b2). libpaper-utils set to manually installed. libyaml-0-2 is already the newest version (0.2.5-2). libyaml-0-2 set to manually installed. node-jed is already the newest version (1.1.1-4). node-jed set to manually installed. r-cran-rlang is already the newest version (1.1.5-3). r-cran-rlang set to manually installed. libreadline8t64 is already the newest version (8.3-2). libreadline8t64 set to manually installed. python3-soupsieve is already the newest version (2.7-2). python3-soupsieve set to manually installed. libtsan2 is already the newest version (15.2.0-2). libtsan2 set to manually installed. libwebp7 is already the newest version (1.5.0-0.1). libwebp7 set to manually installed. libkeyutils1 is already the newest version (1.6.3-6). libkeyutils1 set to manually installed. rpcsvc-proto is already the newest version (1.4.3-1). rpcsvc-proto set to manually installed. python3-zopfli is already the newest version (0.2.3.post1-1+b1). python3-zopfli set to manually installed. util-linux is already the newest version (2.41.1-1). libavif16 is already the newest version (1.3.0-1). libavif16 set to manually installed. python3-terminado is already the newest version (0.18.1-1). python3-terminado set to manually installed. r-base-core is already the newest version (4.5.1-1). r-base-core set to manually installed. libjs-xterm is already the newest version (5.3.0-4). libjs-xterm set to manually installed. libattr1 is already the newest version (1:2.5.2-3). python3-all is already the newest version (3.13.7-1). python3-all set to manually installed. gcc-14-base is already the newest version (14.3.0-5). gcc-14-base set to manually installed. python3-pandas-lib is already the newest version (2.2.3+dfsg-9). python3-pandas-lib set to manually installed. python3-installer is already the newest version (0.7.0+dfsg1-3). python3-installer set to manually installed. libxft2 is already the newest version (2.3.6-1+b4). libxft2 set to manually installed. python-matplotlib-doc is already the newest version (3.10.1+dfsg1-4). python-matplotlib-doc set to manually installed. libtirpc3t64 is already the newest version (1.3.6+ds-1). libtirpc3t64 set to manually installed. libcc1-0 is already the newest version (15.2.0-2). libcc1-0 set to manually installed. libc-bin is already the newest version (2.41-12). docutils-common is already the newest version (0.21.2+dfsg-2). docutils-common set to manually installed. libdebconfclient0 is already the newest version (0.280). libaudit-common is already the newest version (1:4.0.5-1). libunistring5 is already the newest version (1.3-2). libunistring5 set to manually installed. r-cran-cardata is already the newest version (3.0.5-1). r-cran-cardata set to manually installed. libpam-runtime is already the newest version (1.7.0-5). pandoc-data is already the newest version (3.1.11.1-3). pandoc-data set to manually installed. python3-typeguard is already the newest version (4.4.4-1). python3-typeguard set to manually installed. libwebpdemux2 is already the newest version (1.5.0-0.1). libwebpdemux2 set to manually installed. libtasn1-6 is already the newest version (4.20.0-2). libtasn1-6 set to manually installed. python3-wcwidth is already the newest version (0.2.13+dfsg1-1). python3-wcwidth set to manually installed. libcap-ng0 is already the newest version (0.8.5-4+b1). autopoint is already the newest version (0.23.1-2). autopoint set to manually installed. r-cran-guerry is already the newest version (1.8.3-1). r-cran-guerry set to manually installed. libjs-mathjax is already the newest version (2.7.9+dfsg-1). libjs-mathjax set to manually installed. libquadmath0 is already the newest version (15.2.0-2). libquadmath0 set to manually installed. fonts-lyx is already the newest version (2.4.3-1). fonts-lyx set to manually installed. libcamd3 is already the newest version (1:7.11.0+dfsg-1). libcamd3 set to manually installed. python3-yaml is already the newest version (6.0.2-2). python3-yaml set to manually installed. m4 is already the newest version (1.4.19-8). m4 set to manually installed. libgdbm-compat4t64 is already the newest version (1.26-1). libgdbm-compat4t64 set to manually installed. python3-bs4 is already the newest version (4.13.4-4). python3-bs4 set to manually installed. tk8.6-blt2.5 is already the newest version (2.5.3+dfsg-8). tk8.6-blt2.5 set to manually installed. r-cran-fansi is already the newest version (1.0.6-2). r-cran-fansi set to manually installed. libcairo2 is already the newest version (1.18.4-1+b1). libcairo2 set to manually installed. automake is already the newest version (1:1.17-4). automake set to manually installed. libgslcblas0 is already the newest version (2.8+dfsg-5). libgslcblas0 set to manually installed. libelf1t64 is already the newest version (0.192-4). libelf1t64 set to manually installed. liblapack3 is already the newest version (3.12.1-6). liblapack3 set to manually installed. libthai-data is already the newest version (0.1.29-2). libthai-data set to manually installed. gcc-x86-64-linux-gnu is already the newest version (4:14.2.0-1). gcc-x86-64-linux-gnu set to manually installed. libtext-charwidth-perl is already the newest version (0.04-11+b4). libtext-charwidth-perl set to manually installed. libp11-kit0 is already the newest version (0.25.5-3). libp11-kit0 set to manually installed. librtmp1 is already the newest version (2.4+20151223.gitfa8646d.1-3). librtmp1 set to manually installed. python3-pytest is already the newest version (8.4.1-1). python3-pytest set to manually installed. libzopfli1 is already the newest version (1.0.3-3). libzopfli1 set to manually installed. x11-common is already the newest version (1:7.7+24). x11-common set to manually installed. r-cran-backports is already the newest version (1.5.0-2). r-cran-backports set to manually installed. python3-matplotlib is already the newest version (3.10.1+dfsg1-4). python3-matplotlib set to manually installed. libzmq5 is already the newest version (4.3.5-1+b3). libzmq5 set to manually installed. libjs-moment is already the newest version (2.29.4+ds-1). libjs-moment set to manually installed. libglpk40 is already the newest version (5.0-2). libglpk40 set to manually installed. libtk8.6 is already the newest version (8.6.17-1). libtk8.6 set to manually installed. libjs-underscore is already the newest version (1.13.4~dfsg+~1.11.4-3). libjs-underscore set to manually installed. findutils is already the newest version (4.10.0-3). libxext6 is already the newest version (2:1.3.4-1+b3). libxext6 set to manually installed. fonts-font-awesome is already the newest version (5.0.10+really4.7.0~dfsg-4.1). fonts-font-awesome set to manually installed. python3-fastjsonschema is already the newest version (2.21.1-1). python3-fastjsonschema set to manually installed. gzip is already the newest version (1.13-1). libglib2.0-0t64 is already the newest version (2.84.4-3). libglib2.0-0t64 set to manually installed. python3-pickleshare is already the newest version (0.7.5-5). python3-pickleshare set to manually installed. littler is already the newest version (0.3.21-1). littler set to manually installed. libaom3 is already the newest version (3.12.1-1). libaom3 set to manually installed. ncurses-base is already the newest version (6.5+20250216-2). python3-seaborn is already the newest version (0.13.2-5). python3-seaborn set to manually installed. libcap2 is already the newest version (1:2.75-10+b1). libkrb5support0 is already the newest version (1.21.3-5). libkrb5support0 set to manually installed. binutils is already the newest version (2.45-4). binutils set to manually installed. libjs-backbone is already the newest version (1.4.1~dfsg+~1.4.15-3). libjs-backbone set to manually installed. python3-lxml is already the newest version (6.0.1-1). python3-lxml set to manually installed. gcc-14-x86-64-linux-gnu is already the newest version (14.3.0-5). gcc-14-x86-64-linux-gnu set to manually installed. r-cran-vcd is already the newest version (1:1.4-13-1). r-cran-vcd set to manually installed. libbz2-1.0 is already the newest version (1.0.8-6). python3-attr is already the newest version (25.3.0-1). python3-attr set to manually installed. libpangocairo-1.0-0 is already the newest version (1.56.3-1). libpangocairo-1.0-0 set to manually installed. xml-core is already the newest version (0.19). xml-core set to manually installed. r-cran-glue is already the newest version (1.8.0-1). r-cran-glue set to manually installed. libdsdp-5.8t64 is already the newest version (5.8-10.1). libdsdp-5.8t64 set to manually installed. libssh2-1t64 is already the newest version (1.11.1-1). libssh2-1t64 set to manually installed. python3-alabaster is already the newest version (0.7.16-0.1). python3-alabaster set to manually installed. python3-lz4 is already the newest version (4.4.4+dfsg-1). python3-lz4 set to manually installed. libsource-highlight4t64 is already the newest version (3.1.9-4.3+b1). libsource-highlight4t64 set to manually installed. ca-certificates is already the newest version (20250419). ca-certificates set to manually installed. dpkg is already the newest version (1.22.21). python3-dateutil is already the newest version (2.9.0-4). python3-dateutil set to manually installed. python3-ply is already the newest version (3.11-9). python3-ply set to manually installed. libperl5.40 is already the newest version (5.40.1-6). libperl5.40 set to manually installed. liblastlog2-2 is already the newest version (2.41.1-1). libmagic1t64 is already the newest version (1:5.46-5). libmagic1t64 set to manually installed. python3-prometheus-client is already the newest version (0.21.1+ds1-1). python3-prometheus-client set to manually installed. libdebhelper-perl is already the newest version (13.26). libdebhelper-perl set to manually installed. libxcb-shm0 is already the newest version (1.17.0-2+b1). libxcb-shm0 set to manually installed. libbabeltrace1 is already the newest version (1.5.11-4+b2). libbabeltrace1 set to manually installed. libpython3-all-dev is already the newest version (3.13.7-1). libpython3-all-dev set to manually installed. libpython3.13-stdlib is already the newest version (3.13.7-1). libpython3.13-stdlib set to manually installed. make is already the newest version (4.4.1-2). make set to manually installed. libmagic-mgc is already the newest version (1:5.46-5). libmagic-mgc set to manually installed. r-cran-mass is already the newest version (7.3-65-1). r-cran-mass set to manually installed. r-cran-vctrs is already the newest version (0.6.5-1). r-cran-vctrs set to manually installed. gcc is already the newest version (4:14.2.0-1). gcc set to manually installed. python3-colorama is already the newest version (0.4.6-4). python3-colorama set to manually installed. libstdc++-14-dev is already the newest version (14.3.0-5). libstdc++-14-dev set to manually installed. zlib1g-dev is already the newest version (1:1.3.dfsg+really1.3.1-1+b1). zlib1g-dev set to manually installed. build-essential is already the newest version (12.12). build-essential set to manually installed. libfontconfig1 is already the newest version (2.15.0-2.3). libfontconfig1 set to manually installed. libpython3-dev is already the newest version (3.13.7-1). libpython3-dev set to manually installed. libdebuginfod-common is already the newest version (0.192-4). libdebuginfod-common set to manually installed. python3-defusedxml is already the newest version (0.7.1-3). python3-defusedxml set to manually installed. liblsan0 is already the newest version (15.2.0-2). liblsan0 set to manually installed. python-tinycss2-common is already the newest version (1.4.0-2). python-tinycss2-common set to manually installed. gettext is already the newest version (0.23.1-2+b1). gettext set to manually installed. python3-ipykernel is already the newest version (6.30.1-1). python3-ipykernel set to manually installed. python3-pycparser is already the newest version (2.22-2). python3-pycparser set to manually installed. python3-notebook is already the newest version (6.4.13-5). python3-notebook set to manually installed. libjansson4 is already the newest version (2.14-2+b3). libjansson4 set to manually installed. python3-sympy is already the newest version (1.14.0-2). python3-sympy set to manually installed. libltdl7 is already the newest version (2.5.4-4). libltdl7 set to manually installed. libhwasan0 is already the newest version (15.2.0-2). libhwasan0 set to manually installed. gdb is already the newest version (16.3-4). gdb set to manually installed. init-system-helpers is already the newest version (1.69). r-cran-statmod is already the newest version (1.5.0-1). r-cran-statmod set to manually installed. bsdutils is already the newest version (1:2.41.1-1). python3-pandocfilters is already the newest version (1.5.1-1). python3-pandocfilters set to manually installed. python3-py is already the newest version (1.11.0-5). python3-py set to manually installed. cpp is already the newest version (4:14.2.0-1). cpp set to manually installed. python3-kiwisolver is already the newest version (1.4.7-3+b1). python3-kiwisolver set to manually installed. libxt6t64 is already the newest version (1:1.2.1-1.2+b2). libxt6t64 set to manually installed. r-cran-r6 is already the newest version (2.6.1-1). r-cran-r6 set to manually installed. python3-contourpy is already the newest version (1.3.1-2). python3-contourpy set to manually installed. libuuid1 is already the newest version (2.41.1-1). libjodycode3t64 is already the newest version (3.1.2-1). libjodycode3t64 set to manually installed. libmd0 is already the newest version (1.1.0-2+b1). fonts-dejavu-core is already the newest version (2.37-8). fonts-dejavu-core set to manually installed. libgfortran5 is already the newest version (15.2.0-2). libgfortran5 set to manually installed. libyuv0 is already the newest version (0.0.1916.20250814-1). libyuv0 set to manually installed. libnghttp3-9 is already the newest version (1.8.0-1). libnghttp3-9 set to manually installed. libzstd1 is already the newest version (1.5.7+dfsg-1). zip is already the newest version (3.0-15). zip set to manually installed. libdw1t64 is already the newest version (0.192-4). libdw1t64 set to manually installed. python3-fonttools is already the newest version (4.57.0-1). python3-fonttools set to manually installed. python3-wheel is already the newest version (0.46.1-2). python3-wheel set to manually installed. libxdmcp6 is already the newest version (1:1.1.5-1). libxdmcp6 set to manually installed. libumfpack6 is already the newest version (1:7.11.0+dfsg-1). libumfpack6 set to manually installed. liblcms2-2 is already the newest version (2.16-2). liblcms2-2 set to manually installed. libjs-bootstrap is already the newest version (3.4.1+dfsg-6). libjs-bootstrap set to manually installed. diffutils is already the newest version (1:3.10-4). r-cran-magrittr is already the newest version (2.0.3-1). r-cran-magrittr set to manually installed. r-cran-lme4 is already the newest version (1.1-37-1). r-cran-lme4 set to manually installed. python3-cvxopt is already the newest version (1.3.0+dfsg-1+b9). python3-cvxopt set to manually installed. python3-numpydoc is already the newest version (1.9.0-1). python3-numpydoc set to manually installed. pandoc is already the newest version (3.1.11.1+ds-3). pandoc set to manually installed. python3-minimal is already the newest version (3.13.7-1). python3-minimal set to manually installed. libaudit1 is already the newest version (1:4.0.5-1). libc-dev-bin is already the newest version (2.41-12). libc-dev-bin set to manually installed. tzdata is already the newest version (2025b-5). tzdata set to manually installed. python3-jaraco.context is already the newest version (6.0.1-1). python3-jaraco.context set to manually installed. libxss1 is already the newest version (1:1.2.3-1+b3). libxss1 set to manually installed. python3-autocommand is already the newest version (2.2.2-3). python3-autocommand set to manually installed. r-cran-pkgconfig is already the newest version (2.0.3-2). r-cran-pkgconfig set to manually installed. r-cran-cpp11 is already the newest version (0.5.2-1). r-cran-cpp11 set to manually installed. python3-pyparsing is already the newest version (3.1.2-1). python3-pyparsing set to manually installed. fonts-dejavu-mono is already the newest version (2.37-8). fonts-dejavu-mono set to manually installed. base-passwd is already the newest version (3.6.7). perl is already the newest version (5.40.1-6). perl set to manually installed. python3-packaging is already the newest version (25.0-1). python3-packaging set to manually installed. libccolamd3 is already the newest version (1:7.11.0+dfsg-1). libccolamd3 set to manually installed. python3-dev is already the newest version (3.13.7-1). python3-dev set to manually installed. netbase is already the newest version (6.5). netbase set to manually installed. dash is already the newest version (0.5.12-12). dh-strip-nondeterminism is already the newest version (1.14.2-1). dh-strip-nondeterminism set to manually installed. python3.13-doc is already the newest version (3.13.7-1). python3.13-doc set to manually installed. ucf is already the newest version (3.0052). ucf set to manually installed. r-cran-tidyselect is already the newest version (1.2.1+dfsg-1). r-cran-tidyselect set to manually installed. libdav1d7 is already the newest version (1.5.1-1). libdav1d7 set to manually installed. python3-pkg-resources is already the newest version (78.1.1-0.1). python3-pkg-resources set to manually installed. python3-typeshed is already the newest version (0.0~git20241223.ea91db2-3). python3-typeshed set to manually installed. libjs-jed is already the newest version (1.1.1-4). libjs-jed set to manually installed. libssl3t64 is already the newest version (3.5.2-1). python3-charset-normalizer is already the newest version (3.4.3-1). python3-charset-normalizer set to manually installed. xz-utils is already the newest version (5.8.1-1). xz-utils set to manually installed. libpcre2-8-0 is already the newest version (10.45-1). libcolamd3 is already the newest version (1:7.11.0+dfsg-1). libcolamd3 set to manually installed. libitm1 is already the newest version (15.2.0-2). libitm1 set to manually installed. openssl-provider-legacy is already the newest version (3.5.2-1). python3-all-dev is already the newest version (3.13.7-1). python3-all-dev set to manually installed. gettext-base is already the newest version (0.23.1-2+b1). gettext-base set to manually installed. libmount1 is already the newest version (2.41.1-1). python3-pure-eval is already the newest version (0.2.3-1). python3-pure-eval set to manually installed. python-pandas-doc is already the newest version (2.2.3+dfsg-9). python-pandas-doc set to manually installed. r-cran-rbibutils is already the newest version (2.3-1). r-cran-rbibutils set to manually installed. python3-roman is already the newest version (5.1-1). python3-roman set to manually installed. libgomp1 is already the newest version (15.2.0-2). libgomp1 set to manually installed. libpython3-stdlib is already the newest version (3.13.7-1). libpython3-stdlib set to manually installed. r-cran-lmtest is already the newest version (0.9.40-1). r-cran-lmtest set to manually installed. fontconfig is already the newest version (2.15.0-2.3). fontconfig set to manually installed. libtcl8.6 is already the newest version (8.6.17+dfsg-1). libtcl8.6 set to manually installed. python3-joblib is already the newest version (1.4.2-5). python3-joblib set to manually installed. python3-rpds-py is already the newest version (0.21.0-2+b1). python3-rpds-py set to manually installed. r-cran-broom is already the newest version (1.0.7+dfsg-1). r-cran-broom set to manually installed. libblas3 is already the newest version (3.12.1-6). libblas3 set to manually installed. binutils-x86-64-linux-gnu is already the newest version (2.45-4). binutils-x86-64-linux-gnu set to manually installed. libblkid1 is already the newest version (2.41.1-1). libcrypt1 is already the newest version (1:4.4.38-1). libjs-text-encoding is already the newest version (0.7.0-5). libjs-text-encoding set to manually installed. libfreetype6 is already the newest version (2.13.3+dfsg-1). libfreetype6 set to manually installed. grep is already the newest version (3.11-4). jdupes is already the newest version (1.28.0-1). jdupes set to manually installed. r-cran-boot is already the newest version (1.3-31-1). r-cran-boot set to manually installed. r-cran-pillar is already the newest version (1.10.1+dfsg-1). r-cran-pillar set to manually installed. hostname is already the newest version (3.25). python3-iniconfig is already the newest version (1.1.1-2). python3-iniconfig set to manually installed. r-cran-rcpp is already the newest version (1.1.0-1). r-cran-rcpp set to manually installed. python3.13 is already the newest version (3.13.7-1). python3.13 set to manually installed. python3-tk is already the newest version (3.13.5-1). python3-tk set to manually installed. openssl is already the newest version (3.5.2-1). openssl set to manually installed. python3-cffi is already the newest version (2.0.0~b1-1). python3-cffi set to manually installed. r-cran-lifecycle is already the newest version (1.0.4+dfsg-1). r-cran-lifecycle set to manually installed. libx11-6 is already the newest version (2:1.8.12-1). libx11-6 set to manually installed. bzip2 is already the newest version (1.0.8-6). bzip2 set to manually installed. libseccomp2 is already the newest version (2.6.0-2). libseccomp2 set to manually installed. libxslt1.1 is already the newest version (1.1.43-0.2). libxslt1.1 set to manually installed. python3-psutil is already the newest version (7.0.0-2). python3-psutil set to manually installed. r-cran-tidyr is already the newest version (1.3.1-1). r-cran-tidyr set to manually installed. libgav1-1 is already the newest version (0.19.0-3+b1). libgav1-1 set to manually installed. libgnutls30t64 is already the newest version (3.8.10-2). libgnutls30t64 set to manually installed. fonts-mathjax is already the newest version (2.7.9+dfsg-1). fonts-mathjax set to manually installed. liblzma5 is already the newest version (5.8.1-1). libisl23 is already the newest version (0.27-1). libisl23 set to manually installed. python3-tzlocal is already the newest version (5.3.1-1). python3-tzlocal set to manually installed. gcc-15-base is already the newest version (15.2.0-2). bsdextrautils is already the newest version (2.41.1-1). bsdextrautils set to manually installed. libqhull-r8.0 is already the newest version (2020.2-6+b2). libqhull-r8.0 set to manually installed. python3-inflect is already the newest version (7.3.1-2). python3-inflect set to manually installed. python3-mpmath is already the newest version (1.3.0-1). python3-mpmath set to manually installed. python3-nbconvert is already the newest version (7.16.6-1). python3-nbconvert set to manually installed. libdebuginfod1t64 is already the newest version (0.192-4). libdebuginfod1t64 set to manually installed. python3-cffi-backend is already the newest version (2.0.0~b1-1). python3-cffi-backend set to manually installed. libxcb1 is already the newest version (1.17.0-2+b1). libxcb1 set to manually installed. libsm6 is already the newest version (2:1.2.6-1). libsm6 set to manually installed. python3-pyproject-hooks is already the newest version (1.2.0-1). python3-pyproject-hooks set to manually installed. libfftw3-double3 is already the newest version (3.3.10-2+b1). libfftw3-double3 set to manually installed. patch is already the newest version (2.8-2). patch set to manually installed. libpam-modules is already the newest version (1.7.0-5). libjs-jquery-ui is already the newest version (1.13.2+dfsg-1). libjs-jquery-ui set to manually installed. python3-pytz is already the newest version (2025.2-3). python3-pytz set to manually installed. libbsd0 is already the newest version (0.12.2-2). libbsd0 set to manually installed. r-cran-lattice is already the newest version (0.22-7-1). r-cran-lattice set to manually installed. python3-numpy-dev is already the newest version (1:2.2.4+ds-1). python3-numpy-dev set to manually installed. libncursesw6 is already the newest version (6.5+20250216-2). libncursesw6 set to manually installed. libjpeg62-turbo is already the newest version (1:2.1.5-4). libjpeg62-turbo set to manually installed. python-babel-localedata is already the newest version (2.17.0-1). python-babel-localedata set to manually installed. libtinfo6 is already the newest version (6.5+20250216-2). r-cran-rdpack is already the newest version (2.6.3-1). r-cran-rdpack set to manually installed. python3-snowballstemmer is already the newest version (3.0.1-1). python3-snowballstemmer set to manually installed. python3-pluggy is already the newest version (1.6.0-1). python3-pluggy set to manually installed. python3-webencodings is already the newest version (0.5.1-5). python3-webencodings set to manually installed. libpython3.13-minimal is already the newest version (3.13.7-1). libpython3.13-minimal set to manually installed. perl-modules-5.40 is already the newest version (5.40.1-6). perl-modules-5.40 set to manually installed. 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. I: running --customize-hook in shell: sh -c 'chroot "$1" dpkg -r debootsnap-dummy' exec /srv/rebuilderd/tmp/mmdebstrap.Hrzbl74ZXf (Reading database ... 87492 files and directories currently installed.) Removing debootsnap-dummy (1.0) ... I: running --customize-hook in shell: sh -c 'chroot "$1" dpkg-query --showformat '${binary:Package}=${Version}\n' --show > "$1/pkglist"' exec /srv/rebuilderd/tmp/mmdebstrap.Hrzbl74ZXf I: running special hook: download /pkglist ./pkglist I: running --customize-hook in shell: sh -c 'rm "$1/pkglist"' exec /srv/rebuilderd/tmp/mmdebstrap.Hrzbl74ZXf I: running special hook: upload sources.list /etc/apt/sources.list I: waiting for background processes to finish... I: cleaning package lists and apt cache... I: skipping cleanup/reproducible as requested I: creating tarball... I: done I: removing tempdir /srv/rebuilderd/tmp/mmdebstrap.Hrzbl74ZXf... I: success in 180.2294 seconds Downloading dependency 512 of 540: gcc-15-base:amd64=15.2.0-2 Downloading dependency 513 of 540: bsdextrautils:amd64=2.41.1-1 Downloading dependency 514 of 540: libqhull-r8.0:amd64=2020.2-6+b2 Downloading dependency 515 of 540: python3-inflect:amd64=7.3.1-2 Downloading dependency 516 of 540: python3-mpmath:amd64=1.3.0-1 Downloading dependency 517 of 540: python3-nbconvert:amd64=7.16.6-1 Downloading dependency 518 of 540: libdebuginfod1t64:amd64=0.192-4 Downloading dependency 519 of 540: python3-cffi-backend:amd64=2.0.0~b1-1 Downloading dependency 520 of 540: libxcb1:amd64=1.17.0-2+b1 Downloading dependency 521 of 540: libsm6:amd64=2:1.2.6-1 Downloading dependency 522 of 540: python3-pyproject-hooks:amd64=1.2.0-1 Downloading dependency 523 of 540: libfftw3-double3:amd64=3.3.10-2+b1 Downloading dependency 524 of 540: patch:amd64=2.8-2 Downloading dependency 525 of 540: libpam-modules:amd64=1.7.0-5 Downloading dependency 526 of 540: libjs-jquery-ui:amd64=1.13.2+dfsg-1 Downloading dependency 527 of 540: python3-pytz:amd64=2025.2-3 Downloading dependency 528 of 540: libbsd0:amd64=0.12.2-2 Downloading dependency 529 of 540: r-cran-lattice:amd64=0.22-7-1 Downloading dependency 530 of 540: python3-numpy-dev:amd64=1:2.2.4+ds-1 Downloading dependency 531 of 540: libncursesw6:amd64=6.5+20250216-2 Downloading dependency 532 of 540: libjpeg62-turbo:amd64=1:2.1.5-4 Downloading dependency 533 of 540: python-babel-localedata:amd64=2.17.0-1 Downloading dependency 534 of 540: libtinfo6:amd64=6.5+20250216-2 Downloading dependency 535 of 540: r-cran-rdpack:amd64=2.6.3-1 Downloading dependency 536 of 540: python3-snowballstemmer:amd64=3.0.1-1 Downloading dependency 537 of 540: python3-pluggy:amd64=1.6.0-1 Downloading dependency 538 of 540: python3-webencodings:amd64=0.5.1-5 Downloading dependency 539 of 540: libpython3.13-minimal:amd64=3.13.7-1 Downloading dependency 540 of 540: perl-modules-5.40:amd64=5.40.1-6 env --chdir=/srv/rebuilderd/tmp/rebuilderdrdSFyz/out DEB_BUILD_OPTIONS=parallel=6 LANG=C.UTF-8 LC_COLLATE=C.UTF-8 LC_CTYPE=C.UTF-8 SOURCE_DATE_EPOCH=1754831627 SBUILD_CONFIG=/srv/rebuilderd/tmp/debrebuild1KDJYI/debrebuild.sbuildrc.HfvufBbP4gYH sbuild --build=amd64 --host=amd64 --no-source --no-arch-any --arch-all --chroot=/srv/rebuilderd/tmp/debrebuild1KDJYI/debrebuild.tar.mIw_qp9fmnuu --chroot-mode=unshare --dist=unstable --no-run-lintian --no-run-piuparts --no-run-autopkgtest --no-apt-update --no-apt-upgrade --no-apt-distupgrade --verbose --nolog --bd-uninstallable-explainer= --build-path=/build/reproducible-path --dsc-dir=statsmodels-0.14.5+dfsg /srv/rebuilderd/tmp/rebuilderdrdSFyz/inputs/statsmodels_0.14.5+dfsg-1.dsc I: consider moving your ~/.sbuildrc to /srv/rebuilderd/.config/sbuild/config.pl The Debian buildds switched to the "unshare" backend and sbuild will default to it in the future. To start using "unshare" add this to your `~/.config/sbuild/config.pl`: $chroot_mode = "unshare"; If you want to keep the old "schroot" mode even in the future, add the following to your `~/.config/sbuild/config.pl`: $chroot_mode = "schroot"; $schroot = "schroot"; sbuild (Debian sbuild) 0.89.3+deb13u1 (16 August 2025) on ionos23-amd64.debian.net +==============================================================================+ | statsmodels 0.14.5+dfsg-1 (amd64) Thu, 02 Oct 2025 08:39:06 +0000 | +==============================================================================+ Package: statsmodels Version: 0.14.5+dfsg-1 Source Version: 0.14.5+dfsg-1 Distribution: unstable Machine Architecture: amd64 Host Architecture: amd64 Build Architecture: amd64 Build Type: all I: No tarballs found in /srv/rebuilderd/.cache/sbuild I: Unpacking /srv/rebuilderd/tmp/debrebuild1KDJYI/debrebuild.tar.mIw_qp9fmnuu to /srv/rebuilderd/tmp/tmp.sbuild.WQzgGusdGp... I: Setting up the chroot... I: Creating chroot session... I: Setting up log color... I: Setting up apt archive... +------------------------------------------------------------------------------+ | Fetch source files Thu, 02 Oct 2025 08:39:20 +0000 | +------------------------------------------------------------------------------+ Local sources ------------- /srv/rebuilderd/tmp/rebuilderdrdSFyz/inputs/statsmodels_0.14.5+dfsg-1.dsc exists in /srv/rebuilderd/tmp/rebuilderdrdSFyz/inputs; copying to chroot +------------------------------------------------------------------------------+ | Install package build dependencies Thu, 02 Oct 2025 08:39:22 +0000 | +------------------------------------------------------------------------------+ Setup apt archive ----------------- Merged Build-Depends: cython3 (>= 3.0.10~), debhelper-compat (= 13), dh-sequence-numpy3, dh-sequence-python3, dh-sequence-sphinxdoc, pybuild-plugin-pyproject, python3-all-dev, python3-colorama, python3-cvxopt, python3-dateutil, python3-jinja2, python3-joblib, python3-matplotlib, python3-numpy (>= 1:2.0.0~), python3-packaging (>= 21.3~), python3-pandas (>= 1.4~), python3-patsy (>= 0.5.6~), python3-pytest, python3-pytest-forked, python3-scipy (>= 1.13~), python3-setuptools (>= 69.0.2~), python3-setuptools-scm (>= 8~), python3-tk, build-essential, python3-jupyter-client, python3-nbconvert, python3-nbsphinx, python3-notebook, python3-numpydoc, python3-pickleshare, python3-seaborn, python3-simplegeneric, python3-sphinx, python3-yaml, python3-yapf, jdupes, python-matplotlib-doc, python-numpy-doc, python-scipy-doc, python-pandas-doc, python3-doc, r-base-core, python3-rpy2, r-cran-cardata, r-cran-geepack, r-cran-guerry, r-cran-lme4, r-cran-mass, r-cran-robustbase, r-cran-vcd, pandoc Filtered Build-Depends: cython3 (>= 3.0.10~), debhelper-compat (= 13), dh-sequence-numpy3, dh-sequence-python3, dh-sequence-sphinxdoc, pybuild-plugin-pyproject, python3-all-dev, python3-colorama, python3-cvxopt, python3-dateutil, python3-jinja2, python3-joblib, python3-matplotlib, python3-numpy (>= 1:2.0.0~), python3-packaging (>= 21.3~), python3-pandas (>= 1.4~), python3-patsy (>= 0.5.6~), python3-pytest, python3-pytest-forked, python3-scipy (>= 1.13~), python3-setuptools (>= 69.0.2~), python3-setuptools-scm (>= 8~), python3-tk, build-essential, python3-jupyter-client, python3-nbconvert, python3-nbsphinx, python3-notebook, python3-numpydoc, python3-pickleshare, python3-seaborn, python3-simplegeneric, python3-sphinx, python3-yaml, python3-yapf, jdupes, python-matplotlib-doc, python-numpy-doc, python-scipy-doc, python-pandas-doc, python3-doc, r-base-core, python3-rpy2, r-cran-cardata, r-cran-geepack, r-cran-guerry, r-cran-lme4, r-cran-mass, r-cran-robustbase, r-cran-vcd, pandoc dpkg-deb: building package 'sbuild-build-depends-main-dummy' in '/build/reproducible-path/resolver-3fZUCx/apt_archive/sbuild-build-depends-main-dummy.deb'. Install main build dependencies (apt-based resolver) ---------------------------------------------------- Installing build dependencies +------------------------------------------------------------------------------+ | Check architectures Thu, 02 Oct 2025 08:39:26 +0000 | +------------------------------------------------------------------------------+ Arch check ok (amd64 included in any all) +------------------------------------------------------------------------------+ | Build environment Thu, 02 Oct 2025 08:39:26 +0000 | +------------------------------------------------------------------------------+ Kernel: Linux 6.12.48+deb13-cloud-amd64 #1 SMP PREEMPT_DYNAMIC Debian 6.12.48-1 (2025-09-20) amd64 (x86_64) Toolchain package versions: binutils_2.45-4 dpkg-dev_1.22.21 g++-14_14.3.0-5 gcc-14_14.3.0-5 libc6-dev_2.41-12 libstdc++-14-dev_14.3.0-5 libstdc++6_15.2.0-2 linux-libc-dev_6.16.3-1 Package versions: autoconf_2.72-3.1 automake_1:1.17-4 autopoint_0.23.1-2 autotools-dev_20240727.1 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python3-wcwidth_0.2.13+dfsg1-1 python3-webencodings_0.5.1-5 python3-wheel_0.46.1-2 python3-yaml_6.0.2-2 python3-yapf_0.43.0-1 python3-zipp_3.21.0-1 python3-zmq_26.4.0-1 python3-zopfli_0.2.3.post1-1+b1 python3.13_3.13.7-1 python3.13-dev_3.13.7-1 python3.13-doc_3.13.7-1 python3.13-minimal_3.13.7-1 python3.13-tk_3.13.7-1 r-base-core_4.5.1-1 r-cran-backports_1.5.0-2 r-cran-boot_1.3-31-1 r-cran-broom_1.0.7+dfsg-1 r-cran-cardata_3.0.5-1 r-cran-cli_3.6.4-1 r-cran-colorspace_2.1-1+dfsg-1 r-cran-cpp11_0.5.2-1 r-cran-deoptimr_1.1-4-1 r-cran-dplyr_1.1.4-4 r-cran-fansi_1.0.6-2 r-cran-geepack_1.3.12-1 r-cran-generics_0.1.3-1 r-cran-glue_1.8.0-1 r-cran-guerry_1.8.3-1 r-cran-lattice_0.22-7-1 r-cran-lifecycle_1.0.4+dfsg-1 r-cran-littler_0.3.21-1 r-cran-lme4_1.1-37-1 r-cran-lmtest_0.9.40-1 r-cran-magrittr_2.0.3-1 r-cran-mass_7.3-65-1 r-cran-matrix_1.7-4-1 r-cran-minqa_1.2.8-1 r-cran-nlme_3.1.168-1 r-cran-nloptr_2.2.1-2 r-cran-pillar_1.10.1+dfsg-1 r-cran-pkgconfig_2.0.3-2 r-cran-pkgkitten_0.2.4-1 r-cran-purrr_1.0.4-1 r-cran-r6_2.6.1-1 r-cran-rbibutils_2.3-1 r-cran-rcpp_1.1.0-1 r-cran-rcppeigen_0.3.4.0.2-1 r-cran-rdpack_2.6.3-1 r-cran-reformulas_0.4.1-1 r-cran-rlang_1.1.5-3 r-cran-robustbase_0.99-4-1-1 r-cran-sp_1:2.2-0+dfsg-1 r-cran-statmod_1.5.0-1 r-cran-stringi_1.8.4-1+b1 r-cran-stringr_1.5.1-1 r-cran-tibble_3.2.1+dfsg-3 r-cran-tidyr_1.3.1-1 r-cran-tidyselect_1.2.1+dfsg-1 r-cran-utf8_1.2.4-1 r-cran-vcd_1:1.4-13-1 r-cran-vctrs_0.6.5-1 r-cran-withr_3.0.2+dfsg-1 r-cran-zoo_1.8-14-1 readline-common_8.3-2 rpcsvc-proto_1.4.3-1 sed_4.9-2 sensible-utils_0.0.26 sgml-base_1.31+nmu1 sphinx-common_8.2.3-2 sysvinit-utils_3.14-4 tar_1.35+dfsg-3.1 tk8.6-blt2.5_2.5.3+dfsg-8 tzdata_2025b-5 ucf_3.0052 unicode-data_15.1.0-1 unzip_6.0-29 util-linux_2.41.1-1 x11-common_1:7.7+24 xdg-utils_1.2.1-2 xml-core_0.19 xz-utils_5.8.1-1 zip_3.0-15 zlib1g_1:1.3.dfsg+really1.3.1-1+b1 zlib1g-dev_1:1.3.dfsg+really1.3.1-1+b1 +------------------------------------------------------------------------------+ | Build Thu, 02 Oct 2025 08:39:26 +0000 | +------------------------------------------------------------------------------+ Unpack source ------------- -----BEGIN PGP SIGNED MESSAGE----- Hash: SHA512 Format: 3.0 (quilt) Source: statsmodels Binary: python-statsmodels-doc, python3-statsmodels, python3-statsmodels-lib Architecture: any all Version: 0.14.5+dfsg-1 Maintainer: Debian Science Maintainers Uploaders: Yaroslav Halchenko , Michael Hanke , Diane Trout , Rebecca N. Palmer Homepage: https://www.statsmodels.org Standards-Version: 4.7.2 Vcs-Browser: https://salsa.debian.org/science-team/statsmodels Vcs-Git: https://salsa.debian.org/science-team/statsmodels.git Testsuite: autopkgtest Testsuite-Triggers: python3-all, python3-colorama, python3-cvxopt, python3-dateutil, python3-jinja2, python3-joblib, python3-matplotlib, python3-pytest, python3-tk Build-Depends: cython3 (>= 3.0.10~), debhelper-compat (= 13), dh-sequence-numpy3, dh-sequence-python3, dh-sequence-sphinxdoc, pybuild-plugin-pyproject, python3-all-dev, python3-colorama , python3-cvxopt , python3-dateutil , python3-jinja2 , python3-joblib , python3-matplotlib, python3-numpy (>= 1:2.0.0~), python3-packaging (>= 21.3~), python3-pandas (>= 1.4~), python3-patsy (>= 0.5.6~) , python3-pytest , python3-pytest-forked , python3-scipy (>= 1.13~), python3-setuptools (>= 69.0.2~), python3-setuptools-scm (>= 8~), python3-tk Build-Depends-Indep: python3-jupyter-client , python3-nbconvert , python3-nbsphinx , python3-notebook , python3-numpydoc , python3-pickleshare , python3-seaborn , python3-simplegeneric , python3-sphinx , python3-yaml , python3-yapf , jdupes , python-matplotlib-doc , python-numpy-doc , python-scipy-doc , python-pandas-doc , python3-doc , r-base-core , python3-rpy2 , r-cran-cardata , r-cran-geepack , r-cran-guerry , r-cran-lme4 , r-cran-mass , r-cran-robustbase , r-cran-vcd , pandoc Package-List: python-statsmodels-doc deb doc optional arch=all python3-statsmodels deb python optional arch=all python3-statsmodels-lib deb python optional arch=any Checksums-Sha1: 1c09b413c04b1b9382bacb5dd908248f9d50f78c 12137092 statsmodels_0.14.5+dfsg.orig.tar.xz 8806b17c17327174e7ff62449699787807d19d1d 36656 statsmodels_0.14.5+dfsg-1.debian.tar.xz Checksums-Sha256: 45e1017295e4bd2ef4d280bdc40ff076f977deb77fc1eb73a3ca01ea127c952c 12137092 statsmodels_0.14.5+dfsg.orig.tar.xz 7d7bf8809629801e4da718b2795fb5a3b69125bcae7d2f709ef1f851fb1247c3 36656 statsmodels_0.14.5+dfsg-1.debian.tar.xz Files: f4000b4770ca8d1fbc3c64fd87106c51 12137092 statsmodels_0.14.5+dfsg.orig.tar.xz 7e1db7adf3fa96ee424f846f8ccf676b 36656 statsmodels_0.14.5+dfsg-1.debian.tar.xz -----BEGIN PGP SIGNATURE----- iQJMBAEBCgA2FiEEZ8sxEAXE7b4yF1MI3uUNDVZ+omYFAmixv88YHHJlYmVjY2Ff cGFsbWVyQHpvaG8uY29tAAoJEN7lDQ1WfqJm63sP/ig1hTXz4vGP/b6Ps9rOIv59 b7jrZps/jIf7A3iT+gm+8xOeEqhU30JTtAF3TrjE9ZMBMNZXTMvHQuI7/ppVYP7r a2y5jPi3Z+tMdTYXYFIa0wSC6UPJ+WzKgquv3lGMtEDpVFHwhg2YnkQM6/veyzSc 32uXNS1Zxu65XHEUNma6lJcXE0BngHxuOASEoQqwOr381Ax6JsQSxsJQ3sLpHwKm 6EpgkYpvLf5Tw67o2AvBxw1wR8SpmaC3Ut2Qn6MRk9ARhMZ/T05khP9qDlGfY2Lg tytKiRmb/Bch5/0+G/r9dDcJlkOHyFDD7YO02k2+hTsI7Ma+HkPI/9TSWwq8pW2a BkGFdZForr/7R+cT+BgzGUf4e8O6AULhuenLArsPCgKWN5KVghpSbejHqcJkPUNR 9WFpqFfZHk6Umm0Xqdo7g/W2AizB6m5a5yaPmblk08ZrKJc+R4M9vhHfs0qbs95g /kE2w1VcNkV6YBXEY/JCALgSXAXxn4fFcGQCKZ4Hg3CDpo1tzgt2AroHLjLiAbmT 4GRrqh7kXpEnprnGqykRd7tQtpNN2l3ID27hLhW1qKQFGJc0w3VHRdi+A/H/VQpj +yQMEUGrbRpjNURIsw6eOZCf7h7kgfhlabQP1NmyPwkntO2rQDKvEkw0ez8h8tLW ERRI98jUCJXmUnrkSY0u =WUnJ -----END PGP SIGNATURE----- dpkg-source: warning: cannot verify inline signature for ./statsmodels_0.14.5+dfsg-1.dsc: unsupported subcommand dpkg-source: info: extracting statsmodels in /build/reproducible-path/statsmodels-0.14.5+dfsg dpkg-source: info: unpacking statsmodels_0.14.5+dfsg.orig.tar.xz dpkg-source: info: unpacking statsmodels_0.14.5+dfsg-1.debian.tar.xz dpkg-source: info: using patch list from debian/patches/series dpkg-source: info: applying use_cached_datasets.patch dpkg-source: info: applying use_system_inventory.patch dpkg-source: info: applying use_available_data.patch dpkg-source: info: applying i386_loosen_test_tolerances.patch dpkg-source: info: applying python3_shebangs.patch dpkg-source: info: applying use_tmp_path.patch dpkg-source: info: applying no_sphinx_material.patch dpkg-source: info: applying sphinx_reproducibility_and_ignore_errors.patch dpkg-source: info: applying sphinx_local_requirejs.patch dpkg-source: info: applying xfail_no_multiprocessing.patch dpkg-source: info: applying remove_ccbysa_snippet.patch dpkg-source: info: applying 997081_xfail.patch dpkg-source: info: applying xfail_i386_ets.patch dpkg-source: info: applying 1014884_loosen_test_tolerances.patch dpkg-source: info: applying 1020060_loosen_test_tolerance.patch dpkg-source: info: applying mips_ignore_nonwarning.patch dpkg-source: info: applying 1030208_scipy1p10.patch dpkg-source: info: applying mips_armel_ignore_nonconverge.patch dpkg-source: info: applying xfail_out_of_memory.patch dpkg-source: info: applying ignore_armel_nonwarning.patch dpkg-source: info: applying mips_ignore_nan_warnings.patch dpkg-source: info: applying cython3p0_compat.patch dpkg-source: info: applying fix_random_seeds.patch dpkg-source: info: applying xfail_dynamic_factor_news_bigendian.patch dpkg-source: info: applying 1079789_ignore_arm64_nonconvergence.patch Check disk space ---------------- Sufficient free space for build User Environment ---------------- APT_CONFIG=/var/lib/sbuild/apt.conf DEB_BUILD_OPTIONS=parallel=6 HOME=/sbuild-nonexistent LANG=C.UTF-8 LC_ALL=C.UTF-8 LC_COLLATE=C.UTF-8 LC_CTYPE=C.UTF-8 LOGNAME=sbuild PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games SHELL=/bin/sh SOURCE_DATE_EPOCH=1754831627 USER=sbuild dpkg-buildpackage ----------------- Command: dpkg-buildpackage --sanitize-env -us -uc -A dpkg-buildpackage: info: source package statsmodels dpkg-buildpackage: info: source version 0.14.5+dfsg-1 dpkg-buildpackage: info: source distribution unstable dpkg-buildpackage: info: source changed by Rebecca N. Palmer dpkg-source --before-build . debian/rules clean dh clean --buildsystem=pybuild debian/rules override_dh_auto_clean make[1]: Entering directory '/build/reproducible-path/statsmodels-0.14.5+dfsg' # dh_auto_clean would try to run setup.py clean, which fails with a message saying to use git clean instead # we can't do that because the buildds don't get a git repo rm -rf cythonize.dat \ *.egg-info \ *.png \ .pybuild \ .pytest_cache \ build \ docs/build/ \ docs/rehab.table \ docs/salary.table \ docs/source/datasets/generated \ docs/source/examples/notebooks \ docs/source/savefig \ docs/source/dev/generated \ docs/source/datasets/statsmodels.datasets.*.rst \ docs/source/examples/notebooks/generated \ docs/source/examples/index.rst \ examples/executed \ tools/hash_dict.pickle find . -name __pycache__ -print0 | xargs -0 rm -rf find . -name *.pyx -print0 | sed -e "s/\.pyx/.c/g" | xargs -0 rm -f find . -name *.pyx.in -print0 | sed -e "s/\.pyx\.in/.pyx/g" | xargs -0 rm -f : # Remove autogenerated version.py rm -f statsmodels/version.py statsmodels/_version.py docs/source/examples/index.rst make[1]: Leaving directory '/build/reproducible-path/statsmodels-0.14.5+dfsg' dh_autoreconf_clean -O--buildsystem=pybuild dh_clean -O--buildsystem=pybuild debian/rules binary-indep dh binary-indep --buildsystem=pybuild dh_update_autotools_config -i -O--buildsystem=pybuild dh_autoreconf -i -O--buildsystem=pybuild dh_auto_configure -i -O--buildsystem=pybuild debian/rules execute_before_dh_auto_build make[1]: Entering directory '/build/reproducible-path/statsmodels-0.14.5+dfsg' mkdir -p /build/reproducible-path/statsmodels-0.14.5+dfsg/build : # Hardcode backend to Agg to avoid doc build and tests failures echo "backend : Agg" >| /build/reproducible-path/statsmodels-0.14.5+dfsg/build/matplotlibrc make[1]: Leaving directory '/build/reproducible-path/statsmodels-0.14.5+dfsg' dh_auto_build -i -O--buildsystem=pybuild I: pybuild plugin_pyproject:129: Building wheel for python3.13 with "build" module I: pybuild base:311: python3.13 -m build --skip-dependency-check --no-isolation --wheel --outdir /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels * Building wheel... warning: statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.pyx:558:14: Unreachable code warning: statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.pyx:1136:14: Unreachable code warning: statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.pyx:1714:14: Unreachable code warning: statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.pyx:2292:14: Unreachable code Compiling statsmodels/tsa/stl/_stl.pyx because it changed. Compiling statsmodels/tsa/holtwinters/_exponential_smoothers.pyx because it changed. Compiling statsmodels/tsa/exponential_smoothing/_ets_smooth.pyx because it changed. Compiling statsmodels/tsa/_innovations.pyx because it changed. Compiling statsmodels/tsa/regime_switching/_hamilton_filter.pyx because it changed. Compiling statsmodels/tsa/regime_switching/_kim_smoother.pyx because it changed. Compiling statsmodels/tsa/innovations/_arma_innovations.pyx because it changed. Compiling statsmodels/nonparametric/linbin.pyx because it changed. Compiling statsmodels/robust/_qn.pyx because it changed. Compiling statsmodels/nonparametric/_smoothers_lowess.pyx because it changed. Compiling statsmodels/tsa/statespace/_initialization.pyx because it changed. Compiling statsmodels/tsa/statespace/_representation.pyx because it changed. Compiling statsmodels/tsa/statespace/_kalman_filter.pyx because it changed. Compiling statsmodels/tsa/statespace/_filters/_conventional.pyx because it changed. Compiling statsmodels/tsa/statespace/_filters/_inversions.pyx because it changed. Compiling statsmodels/tsa/statespace/_filters/_univariate.pyx because it changed. Compiling statsmodels/tsa/statespace/_filters/_univariate_diffuse.pyx because it changed. Compiling statsmodels/tsa/statespace/_kalman_smoother.pyx because it changed. Compiling statsmodels/tsa/statespace/_smoothers/_alternative.pyx because it changed. Compiling statsmodels/tsa/statespace/_smoothers/_classical.pyx because it changed. Compiling statsmodels/tsa/statespace/_smoothers/_conventional.pyx because it changed. Compiling statsmodels/tsa/statespace/_smoothers/_univariate.pyx because it changed. Compiling statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.pyx because it changed. Compiling statsmodels/tsa/statespace/_simulation_smoother.pyx because it changed. Compiling statsmodels/tsa/statespace/_cfa_simulation_smoother.pyx because it changed. Compiling statsmodels/tsa/statespace/_tools.pyx because it changed. [ 1/26] Cythonizing statsmodels/nonparametric/_smoothers_lowess.pyx [ 2/26] Cythonizing statsmodels/nonparametric/linbin.pyx [ 3/26] Cythonizing statsmodels/robust/_qn.pyx [ 4/26] Cythonizing statsmodels/tsa/_innovations.pyx [ 5/26] Cythonizing statsmodels/tsa/exponential_smoothing/_ets_smooth.pyx [ 6/26] Cythonizing statsmodels/tsa/holtwinters/_exponential_smoothers.pyx [ 7/26] Cythonizing statsmodels/tsa/innovations/_arma_innovations.pyx [ 8/26] Cythonizing statsmodels/tsa/regime_switching/_hamilton_filter.pyx [ 9/26] Cythonizing statsmodels/tsa/regime_switching/_kim_smoother.pyx [10/26] Cythonizing statsmodels/tsa/statespace/_cfa_simulation_smoother.pyx [11/26] Cythonizing statsmodels/tsa/statespace/_filters/_conventional.pyx [12/26] Cythonizing statsmodels/tsa/statespace/_filters/_inversions.pyx [13/26] Cythonizing statsmodels/tsa/statespace/_filters/_univariate.pyx [14/26] Cythonizing statsmodels/tsa/statespace/_filters/_univariate_diffuse.pyx [15/26] Cythonizing statsmodels/tsa/statespace/_initialization.pyx [16/26] Cythonizing statsmodels/tsa/statespace/_kalman_filter.pyx [17/26] Cythonizing statsmodels/tsa/statespace/_kalman_smoother.pyx [18/26] Cythonizing statsmodels/tsa/statespace/_representation.pyx [19/26] Cythonizing statsmodels/tsa/statespace/_simulation_smoother.pyx [20/26] Cythonizing statsmodels/tsa/statespace/_smoothers/_alternative.pyx [21/26] Cythonizing statsmodels/tsa/statespace/_smoothers/_classical.pyx [22/26] Cythonizing statsmodels/tsa/statespace/_smoothers/_conventional.pyx [23/26] Cythonizing statsmodels/tsa/statespace/_smoothers/_univariate.pyx [24/26] Cythonizing statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.pyx [25/26] Cythonizing statsmodels/tsa/statespace/_tools.pyx [26/26] Cythonizing statsmodels/tsa/stl/_stl.pyx /usr/lib/python3/dist-packages/setuptools/dist.py:759: SetuptoolsDeprecationWarning: License classifiers are deprecated. !! ******************************************************************************** Please consider removing the following classifiers in favor of a SPDX license expression: License :: OSI Approved :: BSD License See https://packaging.python.org/en/latest/guides/writing-pyproject-toml/#license for details. ******************************************************************************** !! self._finalize_license_expression() running bdist_wheel running build running build_py creating build/lib.linux-x86_64-cpython-313/statsmodels copying statsmodels/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels copying statsmodels/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels copying statsmodels/_version.py -> build/lib.linux-x86_64-cpython-313/statsmodels copying statsmodels/conftest.py -> build/lib.linux-x86_64-cpython-313/statsmodels creating build/lib.linux-x86_64-cpython-313/statsmodels/treatment copying statsmodels/treatment/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/treatment copying statsmodels/treatment/treatment_effects.py -> build/lib.linux-x86_64-cpython-313/statsmodels/treatment creating build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/gof.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/moment_helpers.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/anova.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/rates.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/contrast.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/sandwich_covariance.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/_lilliefors.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/power.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/multivariate.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/regularized_covariance.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/contingency_tables.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/inter_rater.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/_inference_tools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/robust_compare.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/multicomp.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/mediation.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/weightstats.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/oneway.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/_delta_method.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/descriptivestats.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/oaxaca.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/outliers_influence.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/proportion.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/correlation_tools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/effect_size.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/_adnorm.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/meta_analysis.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/diagnostic.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/stattools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/multivariate_tools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/_knockoff.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/base.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/nonparametric.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/multitest.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/_lilliefors_critical_values.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/knockoff_regeffects.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/_diagnostic_other.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/diagnostic_gen.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/tabledist.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats copying statsmodels/stats/dist_dependence_measures.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats creating build/lib.linux-x86_64-cpython-313/statsmodels/src copying statsmodels/src/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/src creating build/lib.linux-x86_64-cpython-313/statsmodels/interface copying statsmodels/interface/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/interface creating build/lib.linux-x86_64-cpython-313/statsmodels/formula copying statsmodels/formula/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/formula copying statsmodels/formula/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/formula copying statsmodels/formula/formulatools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/formula creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa copying statsmodels/tsa/adfvalues.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa copying statsmodels/tsa/arma_mle.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa copying statsmodels/tsa/ar_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa copying statsmodels/tsa/x13.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa copying statsmodels/tsa/varma_process.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa copying statsmodels/tsa/descriptivestats.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa copying statsmodels/tsa/arima_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa copying statsmodels/tsa/mlemodel.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa copying statsmodels/tsa/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa copying statsmodels/tsa/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa copying statsmodels/tsa/stattools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa copying statsmodels/tsa/deterministic.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa copying statsmodels/tsa/tsatools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa copying statsmodels/tsa/arima_process.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa copying statsmodels/tsa/seasonal.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa copying statsmodels/tsa/_bds.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa copying statsmodels/tsa/coint_tables.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa creating build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/optimizer.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/_screening.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/_parameter_inference.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/elastic_net.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/transform.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/wrapper.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/_prediction_inference.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/l1_cvxopt.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/_penalties.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/_constraints.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/covtype.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/_penalized.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/l1_solvers_common.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/distributed_estimation.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base copying statsmodels/base/l1_slsqp.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base creating build/lib.linux-x86_64-cpython-313/statsmodels/compat copying statsmodels/compat/patsy.py -> build/lib.linux-x86_64-cpython-313/statsmodels/compat copying statsmodels/compat/pandas.py -> build/lib.linux-x86_64-cpython-313/statsmodels/compat copying statsmodels/compat/scipy.py -> build/lib.linux-x86_64-cpython-313/statsmodels/compat copying statsmodels/compat/python.py -> build/lib.linux-x86_64-cpython-313/statsmodels/compat copying statsmodels/compat/_scipy_multivariate_t.py -> build/lib.linux-x86_64-cpython-313/statsmodels/compat copying statsmodels/compat/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/compat copying statsmodels/compat/numpy.py -> build/lib.linux-x86_64-cpython-313/statsmodels/compat copying statsmodels/compat/platform.py -> build/lib.linux-x86_64-cpython-313/statsmodels/compat copying statsmodels/compat/pytest.py -> build/lib.linux-x86_64-cpython-313/statsmodels/compat creating build/lib.linux-x86_64-cpython-313/statsmodels/regression copying statsmodels/regression/_prediction.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression copying statsmodels/regression/quantile_regression.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression copying statsmodels/regression/dimred.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression copying statsmodels/regression/mixed_linear_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression copying statsmodels/regression/recursive_ls.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression copying statsmodels/regression/feasible_gls.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression copying statsmodels/regression/rolling.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression copying statsmodels/regression/linear_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression copying statsmodels/regression/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression copying statsmodels/regression/_tools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression copying statsmodels/regression/process_regression.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression creating build/lib.linux-x86_64-cpython-313/statsmodels/discrete copying statsmodels/discrete/discrete_margins.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete copying statsmodels/discrete/discrete_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete copying statsmodels/discrete/truncated_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete copying statsmodels/discrete/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete copying statsmodels/discrete/diagnostic.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete copying statsmodels/discrete/conditional_models.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete copying statsmodels/discrete/_diagnostics_count.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete copying statsmodels/discrete/count_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete creating build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/decorators.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/numdiff.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/rootfinding.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/grouputils.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/sm_exceptions.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/eval_measures.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/web.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/testing.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/typing.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/_test_runner.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/catadd.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/tools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/parallel.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/transform_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/docstring.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/print_version.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/rng_qrng.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/_testing.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/linalg.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools copying statsmodels/tools/sequences.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools creating build/lib.linux-x86_64-cpython-313/statsmodels/distributions copying statsmodels/distributions/empirical_distribution.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions copying statsmodels/distributions/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions copying statsmodels/distributions/tools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions copying statsmodels/distributions/bernstein.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions copying statsmodels/distributions/discrete.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions copying statsmodels/distributions/edgeworth.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions copying statsmodels/distributions/mixture_rvs.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions creating build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels copying statsmodels/miscmodels/count.py -> build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels copying statsmodels/miscmodels/try_mlecov.py -> build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels copying statsmodels/miscmodels/ordinal_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels copying statsmodels/miscmodels/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels copying statsmodels/miscmodels/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels copying statsmodels/miscmodels/tmodel.py -> build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels copying statsmodels/miscmodels/nonlinls.py -> build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels creating build/lib.linux-x86_64-cpython-313/statsmodels/gam copying statsmodels/gam/generalized_additive_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/gam copying statsmodels/gam/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/gam copying statsmodels/gam/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/gam copying statsmodels/gam/smooth_basis.py -> build/lib.linux-x86_64-cpython-313/statsmodels/gam copying statsmodels/gam/gam_penalties.py -> build/lib.linux-x86_64-cpython-313/statsmodels/gam creating build/lib.linux-x86_64-cpython-313/statsmodels/othermod copying statsmodels/othermod/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/othermod copying statsmodels/othermod/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/othermod copying statsmodels/othermod/betareg.py -> build/lib.linux-x86_64-cpython-313/statsmodels/othermod creating build/lib.linux-x86_64-cpython-313/statsmodels/duration copying statsmodels/duration/_kernel_estimates.py -> build/lib.linux-x86_64-cpython-313/statsmodels/duration copying statsmodels/duration/hazard_regression.py -> build/lib.linux-x86_64-cpython-313/statsmodels/duration copying statsmodels/duration/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/duration copying statsmodels/duration/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/duration copying statsmodels/duration/survfunc.py -> build/lib.linux-x86_64-cpython-313/statsmodels/duration creating build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric copying statsmodels/nonparametric/kernel_density.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric copying statsmodels/nonparametric/kernel_regression.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric copying statsmodels/nonparametric/kernels_asymmetric.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric copying statsmodels/nonparametric/kdetools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric copying statsmodels/nonparametric/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric copying statsmodels/nonparametric/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric copying statsmodels/nonparametric/smoothers_lowess_old.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric copying statsmodels/nonparametric/_kernel_base.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric copying statsmodels/nonparametric/smoothers_lowess.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric copying statsmodels/nonparametric/kernels.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric copying statsmodels/nonparametric/kde.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric copying statsmodels/nonparametric/bandwidths.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric creating build/lib.linux-x86_64-cpython-313/statsmodels/emplike copying statsmodels/emplike/aft_el.py -> build/lib.linux-x86_64-cpython-313/statsmodels/emplike copying statsmodels/emplike/descriptive.py -> build/lib.linux-x86_64-cpython-313/statsmodels/emplike copying statsmodels/emplike/originregress.py -> build/lib.linux-x86_64-cpython-313/statsmodels/emplike copying statsmodels/emplike/elregress.py -> build/lib.linux-x86_64-cpython-313/statsmodels/emplike copying statsmodels/emplike/elanova.py -> build/lib.linux-x86_64-cpython-313/statsmodels/emplike copying statsmodels/emplike/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/emplike copying statsmodels/emplike/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/emplike creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets copying statsmodels/datasets/template_data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets copying statsmodels/datasets/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets copying statsmodels/datasets/utils.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets creating build/lib.linux-x86_64-cpython-313/statsmodels/imputation copying statsmodels/imputation/mice.py -> build/lib.linux-x86_64-cpython-313/statsmodels/imputation copying statsmodels/imputation/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/imputation copying statsmodels/imputation/ros.py -> build/lib.linux-x86_64-cpython-313/statsmodels/imputation copying statsmodels/imputation/bayes_mi.py -> build/lib.linux-x86_64-cpython-313/statsmodels/imputation creating build/lib.linux-x86_64-cpython-313/statsmodels/graphics copying statsmodels/graphics/tsaplots.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics copying statsmodels/graphics/_regressionplots_doc.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics copying statsmodels/graphics/functional.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics copying statsmodels/graphics/agreement.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics copying statsmodels/graphics/regressionplots.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics copying statsmodels/graphics/factorplots.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics copying statsmodels/graphics/plot_grids.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics copying statsmodels/graphics/correlation.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics copying statsmodels/graphics/gofplots.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics copying statsmodels/graphics/boxplots.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics copying statsmodels/graphics/plottools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics copying statsmodels/graphics/tukeyplot.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics copying statsmodels/graphics/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics copying statsmodels/graphics/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics copying statsmodels/graphics/mosaicplot.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics copying statsmodels/graphics/dotplots.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics copying statsmodels/graphics/utils.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox copying statsmodels/sandbox/pca.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox copying statsmodels/sandbox/descstats.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox copying statsmodels/sandbox/bspline.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox copying statsmodels/sandbox/multilinear.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox copying statsmodels/sandbox/infotheo.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox copying statsmodels/sandbox/rls.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox copying statsmodels/sandbox/gam.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox copying statsmodels/sandbox/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox copying statsmodels/sandbox/sysreg.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox copying statsmodels/sandbox/mle.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox copying statsmodels/sandbox/predict_functional.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox creating build/lib.linux-x86_64-cpython-313/statsmodels/robust copying statsmodels/robust/norms.py -> build/lib.linux-x86_64-cpython-313/statsmodels/robust copying statsmodels/robust/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/robust copying statsmodels/robust/scale.py -> build/lib.linux-x86_64-cpython-313/statsmodels/robust copying statsmodels/robust/robust_linear_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/robust creating build/lib.linux-x86_64-cpython-313/statsmodels/genmod copying statsmodels/genmod/cov_struct.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod copying statsmodels/genmod/generalized_linear_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod copying statsmodels/genmod/bayes_mixed_glm.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod copying statsmodels/genmod/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod copying statsmodels/genmod/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod copying statsmodels/genmod/qif.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod copying statsmodels/genmod/generalized_estimating_equations.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod copying statsmodels/genmod/_tweedie_compound_poisson.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod creating build/lib.linux-x86_64-cpython-313/statsmodels/multivariate copying statsmodels/multivariate/pca.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate copying statsmodels/multivariate/multivariate_ols.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate copying statsmodels/multivariate/factor.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate copying statsmodels/multivariate/cancorr.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate copying statsmodels/multivariate/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate copying statsmodels/multivariate/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate copying statsmodels/multivariate/plots.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate copying statsmodels/multivariate/manova.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate creating build/lib.linux-x86_64-cpython-313/statsmodels/tests copying statsmodels/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tests copying statsmodels/tests/test_x13.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tests copying statsmodels/tests/test_package.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/iolib copying statsmodels/iolib/summary.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib copying statsmodels/iolib/foreign.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib copying statsmodels/iolib/summary2.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib copying statsmodels/iolib/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib copying statsmodels/iolib/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib copying statsmodels/iolib/openfile.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib copying statsmodels/iolib/table.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib copying statsmodels/iolib/tableformatting.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib copying statsmodels/iolib/smpickle.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib copying statsmodels/iolib/stata_summary_examples.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib creating build/lib.linux-x86_64-cpython-313/statsmodels/treatment/tests copying statsmodels/treatment/tests/test_teffects.py -> build/lib.linux-x86_64-cpython-313/statsmodels/treatment/tests copying statsmodels/treatment/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/treatment/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/treatment/tests/results copying statsmodels/treatment/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/treatment/tests/results copying statsmodels/treatment/tests/results/results_teffects.py -> build/lib.linux-x86_64-cpython-313/statsmodels/treatment/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng copying statsmodels/stats/libqsturng/make_tbls.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng copying statsmodels/stats/libqsturng/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng copying statsmodels/stats/libqsturng/qsturng_.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng creating build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_power.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_multi.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_anova_rm.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_correlation.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_statstools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_base.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_rates_poisson.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_corrpsd.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_lilliefors.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_mediation.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_diagnostic.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_oaxaca.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_tost.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_multivariate.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_gof.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_influence.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_proportion.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_robust_compare.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_nonparametric.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_dist_dependant_measures.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_groups_sw.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_anova.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_meta.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_tabledist.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_sandwich.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_diagnostic_other.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_knockoff.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_outliers_influence.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_moment_helpers.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_contrast.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_contingency_tables.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_descriptivestats.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_deltacov.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_regularized_covariance.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_panel_robustcov.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_effectsize.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_oneway.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_qsturng.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_pairwise.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_inter_rater.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/tests/test_weightstats.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng/tests copying statsmodels/stats/libqsturng/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng/tests copying statsmodels/stats/libqsturng/tests/test_qsturng.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/results_proportion.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/results_meta.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/lilliefors_critical_value_simulation.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/results_power.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/results_panelrobust.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/results_rates.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/results_multinomial_proportions.py -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/formula/tests copying statsmodels/formula/tests/test_formula.py -> build/lib.linux-x86_64-cpython-313/statsmodels/formula/tests copying statsmodels/formula/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/formula/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima copying statsmodels/tsa/arima/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima copying statsmodels/tsa/arima/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima copying statsmodels/tsa/arima/model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima copying statsmodels/tsa/arima/tools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima copying statsmodels/tsa/arima/specification.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima copying statsmodels/tsa/arima/params.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/kalman_smoother.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/_pykalman_smoother.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/initialization.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/kalman_filter.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/sarimax.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/structural.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/representation.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/cfa_simulation_smoother.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/mlemodel.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/simulation_smoother.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/dynamic_factor.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/tools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/exponential_smoothing.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/dynamic_factor_mq.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/_quarterly_ar1.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/news.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace copying statsmodels/tsa/statespace/varmax.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl copying statsmodels/tsa/ardl/pss_critical_values.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl copying statsmodels/tsa/ardl/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl copying statsmodels/tsa/ardl/model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters copying statsmodels/tsa/holtwinters/_smoothers.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters copying statsmodels/tsa/holtwinters/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters copying statsmodels/tsa/holtwinters/model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters copying statsmodels/tsa/holtwinters/results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/innovations copying statsmodels/tsa/innovations/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/innovations copying statsmodels/tsa/innovations/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/innovations copying statsmodels/tsa/innovations/arma_innovations.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/innovations creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl copying statsmodels/tsa/stl/mstl.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl copying statsmodels/tsa/stl/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base copying statsmodels/tsa/base/tsa_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base copying statsmodels/tsa/base/datetools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base copying statsmodels/tsa/base/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base copying statsmodels/tsa/base/prediction.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/forecasting copying statsmodels/tsa/forecasting/stl.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/forecasting copying statsmodels/tsa/forecasting/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/forecasting copying statsmodels/tsa/forecasting/theta.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/forecasting creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching copying statsmodels/tsa/regime_switching/markov_autoregression.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching copying statsmodels/tsa/regime_switching/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching copying statsmodels/tsa/regime_switching/markov_regression.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching copying statsmodels/tsa/regime_switching/markov_switching.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar copying statsmodels/tsa/vector_ar/svar_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar copying statsmodels/tsa/vector_ar/irf.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar copying statsmodels/tsa/vector_ar/var_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar copying statsmodels/tsa/vector_ar/hypothesis_test_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar copying statsmodels/tsa/vector_ar/util.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar copying statsmodels/tsa/vector_ar/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar copying statsmodels/tsa/vector_ar/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar copying statsmodels/tsa/vector_ar/plotting.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar copying statsmodels/tsa/vector_ar/output.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar copying statsmodels/tsa/vector_ar/vecm.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/interp copying statsmodels/tsa/interp/denton.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/interp copying statsmodels/tsa/interp/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/interp creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters copying statsmodels/tsa/filters/cf_filter.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters copying statsmodels/tsa/filters/bk_filter.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters copying statsmodels/tsa/filters/hp_filter.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters copying statsmodels/tsa/filters/filtertools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters copying statsmodels/tsa/filters/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters copying statsmodels/tsa/filters/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters copying statsmodels/tsa/filters/_utils.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/exponential_smoothing copying statsmodels/tsa/exponential_smoothing/initialization.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/exponential_smoothing copying statsmodels/tsa/exponential_smoothing/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/exponential_smoothing copying statsmodels/tsa/exponential_smoothing/base.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/exponential_smoothing copying statsmodels/tsa/exponential_smoothing/ets.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/exponential_smoothing creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests copying statsmodels/tsa/tests/test_arima_process.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests copying statsmodels/tsa/tests/test_ar.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests copying statsmodels/tsa/tests/test_stattools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests copying statsmodels/tsa/tests/test_adfuller_lag.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests copying statsmodels/tsa/tests/test_exponential_smoothing.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests copying statsmodels/tsa/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests copying statsmodels/tsa/tests/test_seasonal.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests copying statsmodels/tsa/tests/test_x13.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests copying statsmodels/tsa/tests/test_deterministic.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests copying statsmodels/tsa/tests/test_tsa_tools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests copying statsmodels/tsa/tests/test_bds.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators copying statsmodels/tsa/arima/estimators/durbin_levinson.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators copying statsmodels/tsa/arima/estimators/statespace.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators copying statsmodels/tsa/arima/estimators/gls.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators copying statsmodels/tsa/arima/estimators/yule_walker.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators copying statsmodels/tsa/arima/estimators/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators copying statsmodels/tsa/arima/estimators/burg.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators copying statsmodels/tsa/arima/estimators/innovations.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators copying statsmodels/tsa/arima/estimators/hannan_rissanen.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/datasets copying statsmodels/tsa/arima/datasets/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/datasets creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/tests copying statsmodels/tsa/arima/tests/test_params.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/tests copying statsmodels/tsa/arima/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/tests copying statsmodels/tsa/arima/tests/test_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/tests copying statsmodels/tsa/arima/tests/test_specification.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/tests copying statsmodels/tsa/arima/tests/test_tools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/tests copying statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/tests copying statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/tests copying statsmodels/tsa/arima/estimators/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/tests copying statsmodels/tsa/arima/estimators/tests/test_innovations.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/tests copying statsmodels/tsa/arima/estimators/tests/test_gls.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/tests copying statsmodels/tsa/arima/estimators/tests/test_statespace.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/tests copying statsmodels/tsa/arima/estimators/tests/test_burg.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/tests copying statsmodels/tsa/arima/estimators/tests/test_yule_walker.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/datasets/brockwell_davis_2002 copying statsmodels/tsa/arima/datasets/brockwell_davis_2002/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/datasets/brockwell_davis_2002 creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/datasets/brockwell_davis_2002/data copying statsmodels/tsa/arima/datasets/brockwell_davis_2002/data/lake.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/datasets/brockwell_davis_2002/data copying statsmodels/tsa/arima/datasets/brockwell_davis_2002/data/sbl.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/datasets/brockwell_davis_2002/data copying statsmodels/tsa/arima/datasets/brockwell_davis_2002/data/oshorts.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/datasets/brockwell_davis_2002/data copying statsmodels/tsa/arima/datasets/brockwell_davis_2002/data/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/datasets/brockwell_davis_2002/data copying statsmodels/tsa/arima/datasets/brockwell_davis_2002/data/dowj.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/datasets/brockwell_davis_2002/data creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters copying statsmodels/tsa/statespace/_filters/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers copying statsmodels/tsa/statespace/_smoothers/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_decompose.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_kalman.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_fixed_params.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_save.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_news.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/kfas_helpers.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_impulse_responses.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_prediction.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_pickle.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_simulation_smoothing.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_cfa_tvpvar.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_representation.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_concentrated.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_options.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_chandrasekhar.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_initialization.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_structural.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_exponential_smoothing.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_models.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_weights.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_conserve_memory.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_collapsed.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_sarimax.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_forecasting.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_univariate.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_smoothing.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_var.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_varmax.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_dynamic_factor.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_mlemodel.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_tools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_simulate.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests copying statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_sarimax.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_varmax.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_var_misc.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_structural.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_dynamic_factor.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_kalman_filter.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_var_R.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/functions copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/functions/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/functions creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data/US copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data/US/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data/US creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl/_pss_critical_values copying statsmodels/tsa/ardl/_pss_critical_values/pss.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl/_pss_critical_values copying statsmodels/tsa/ardl/_pss_critical_values/pss-process.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl/_pss_critical_values copying statsmodels/tsa/ardl/_pss_critical_values/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl/_pss_critical_values creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl/tests copying statsmodels/tsa/ardl/tests/test_ardl.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl/tests copying statsmodels/tsa/ardl/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/tests copying statsmodels/tsa/holtwinters/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/tests copying statsmodels/tsa/holtwinters/tests/test_holtwinters.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/tests/results copying statsmodels/tsa/holtwinters/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/innovations/tests copying statsmodels/tsa/innovations/tests/test_arma_innovations.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/innovations/tests copying statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/innovations/tests copying statsmodels/tsa/innovations/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/innovations/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests copying statsmodels/tsa/stl/tests/test_stl.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests copying statsmodels/tsa/stl/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests copying statsmodels/tsa/stl/tests/test_mstl.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests/results copying statsmodels/tsa/stl/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base/tests copying statsmodels/tsa/base/tests/test_base.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base/tests copying statsmodels/tsa/base/tests/test_prediction.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base/tests copying statsmodels/tsa/base/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base/tests copying statsmodels/tsa/base/tests/test_datetools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base/tests copying statsmodels/tsa/base/tests/test_tsa_indexes.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/forecasting/tests copying statsmodels/tsa/forecasting/tests/test_stl.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/forecasting/tests copying statsmodels/tsa/forecasting/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/forecasting/tests copying statsmodels/tsa/forecasting/tests/test_theta.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/forecasting/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests copying statsmodels/tsa/regime_switching/tests/test_markov_regression.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests copying statsmodels/tsa/regime_switching/tests/test_markov_switching.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests copying statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests copying statsmodels/tsa/regime_switching/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests/results copying statsmodels/tsa/regime_switching/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests copying statsmodels/tsa/vector_ar/tests/example_svar.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests copying statsmodels/tsa/vector_ar/tests/test_var_jmulti.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests copying statsmodels/tsa/vector_ar/tests/test_coint.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests copying statsmodels/tsa/vector_ar/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests copying statsmodels/tsa/vector_ar/tests/test_svar.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests copying statsmodels/tsa/vector_ar/tests/test_vecm.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests copying statsmodels/tsa/vector_ar/tests/test_var.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/parse_jmulti_vecm_output.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/parse_jmulti_var_output.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results copying statsmodels/tsa/vector_ar/tests/results/results_svar_st.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results copying statsmodels/tsa/vector_ar/tests/results/results_var_data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results copying statsmodels/tsa/vector_ar/tests/results/results_var.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results copying statsmodels/tsa/vector_ar/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results copying statsmodels/tsa/vector_ar/tests/results/results_svar.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/Matlab_results copying statsmodels/tsa/vector_ar/tests/Matlab_results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/Matlab_results creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/interp/tests copying statsmodels/tsa/interp/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/interp/tests copying statsmodels/tsa/interp/tests/test_denton.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/interp/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters/tests copying statsmodels/tsa/filters/tests/test_filters.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters/tests copying statsmodels/tsa/filters/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters/tests/results copying statsmodels/tsa/filters/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters/tests/results copying statsmodels/tsa/filters/tests/results/filter_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/arima111_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/arima111nc_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/arima112nc_css_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/results_arma.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/results_process.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/arima112nc_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/savedrvs.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/results_arma_acf.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/arima211nc_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/results_arima.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/arima211nc_css_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/arima111_css_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/arima112_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/arima211_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/arima211_css_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/arima111nc_css_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/arima112_css_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/make_arma.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/results_ar.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/datamlw_tls.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/base/tests copying statsmodels/base/tests/test_data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base/tests copying statsmodels/base/tests/test_penalized.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base/tests copying statsmodels/base/tests/test_optimize.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base/tests copying statsmodels/base/tests/test_predict.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base/tests copying statsmodels/base/tests/test_screening.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base/tests copying statsmodels/base/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base/tests copying statsmodels/base/tests/test_generic_methods.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base/tests copying statsmodels/base/tests/test_transform.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base/tests copying statsmodels/base/tests/test_shrink_pickle.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base/tests copying statsmodels/base/tests/test_distributed_estimation.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base/tests copying statsmodels/base/tests/test_penalties.py -> build/lib.linux-x86_64-cpython-313/statsmodels/base/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/compat/tests copying statsmodels/compat/tests/test_itercompat.py -> build/lib.linux-x86_64-cpython-313/statsmodels/compat/tests copying statsmodels/compat/tests/test_scipy_compat.py -> build/lib.linux-x86_64-cpython-313/statsmodels/compat/tests copying statsmodels/compat/tests/test_pandas.py -> build/lib.linux-x86_64-cpython-313/statsmodels/compat/tests copying statsmodels/compat/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/compat/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests copying statsmodels/regression/tests/test_dimred.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests copying statsmodels/regression/tests/test_recursive_ls.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests copying statsmodels/regression/tests/test_theil.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests copying statsmodels/regression/tests/test_glsar_gretl.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests copying statsmodels/regression/tests/test_predict.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests copying statsmodels/regression/tests/test_rolling.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests copying statsmodels/regression/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests copying statsmodels/regression/tests/test_glsar_stata.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests copying statsmodels/regression/tests/test_processreg.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests copying statsmodels/regression/tests/test_lme.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests copying statsmodels/regression/tests/test_regression.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests copying statsmodels/regression/tests/test_robustcov.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests copying statsmodels/regression/tests/test_quantile_regression.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests copying statsmodels/regression/tests/test_cov.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests copying statsmodels/regression/tests/test_tools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/generate_lme.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/results_quantile_regression.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/macro_gr_corc_stata.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/results_theil_textile.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/lme_r_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/results_macro_ols_robust.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/generate_lasso.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/glmnet_r_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/results_grunfeld_ols_robust_cluster.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/results_regression.py -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests copying statsmodels/discrete/tests/test_truncated_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests copying statsmodels/discrete/tests/test_constrained.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests copying statsmodels/discrete/tests/test_diagnostic.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests copying statsmodels/discrete/tests/test_predict.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests copying statsmodels/discrete/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests copying statsmodels/discrete/tests/test_conditional.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests copying statsmodels/discrete/tests/test_discrete.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests copying statsmodels/discrete/tests/test_margins.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests copying statsmodels/discrete/tests/test_sandwich_cov.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests copying statsmodels/discrete/tests/test_count_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/results_truncated.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/results_glm_logit_constrained.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/results_predict.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/results_count_margins.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/results_truncated_st.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/results_count_robust_cluster.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/results_poisson_constrained.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/results_discrete.py -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/tools/validation copying statsmodels/tools/validation/decorators.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/validation copying statsmodels/tools/validation/validation.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/validation copying statsmodels/tools/validation/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/validation creating build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests copying statsmodels/tools/tests/test_linalg.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests copying statsmodels/tools/tests/test_catadd.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests copying statsmodels/tools/tests/test_data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests copying statsmodels/tools/tests/test_eval_measures.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests copying statsmodels/tools/tests/test_testing.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests copying statsmodels/tools/tests/test_sequences.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests copying statsmodels/tools/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests copying statsmodels/tools/tests/test_decorators.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests copying statsmodels/tools/tests/test_web.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests copying statsmodels/tools/tests/test_transform_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests copying statsmodels/tools/tests/test_grouputils.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests copying statsmodels/tools/tests/test_parallel.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests copying statsmodels/tools/tests/test_numdiff.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests copying statsmodels/tools/tests/test_tools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests copying statsmodels/tools/tests/test_docstring.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests copying statsmodels/tools/tests/test_rootfinding.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/tools/validation/tests copying statsmodels/tools/validation/tests/test_validation.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/validation/tests copying statsmodels/tools/validation/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/tools/validation/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula copying statsmodels/distributions/copula/copulas.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula copying statsmodels/distributions/copula/_special.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula copying statsmodels/distributions/copula/extreme_value.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula copying statsmodels/distributions/copula/transforms.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula copying statsmodels/distributions/copula/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula copying statsmodels/distributions/copula/api.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula copying statsmodels/distributions/copula/archimedean.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula copying statsmodels/distributions/copula/depfunc_ev.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula copying statsmodels/distributions/copula/elliptical.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula copying statsmodels/distributions/copula/other_copulas.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula creating build/lib.linux-x86_64-cpython-313/statsmodels/distributions/tests copying statsmodels/distributions/tests/test_ecdf.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions/tests copying statsmodels/distributions/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions/tests copying statsmodels/distributions/tests/test_discrete.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions/tests copying statsmodels/distributions/tests/test_bernstein.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions/tests copying statsmodels/distributions/tests/test_edgeworth.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions/tests copying statsmodels/distributions/tests/test_mixture.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions/tests copying statsmodels/distributions/tests/test_tools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/distributions/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests copying statsmodels/miscmodels/tests/results_tmodel.py -> build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests copying statsmodels/miscmodels/tests/test_generic_mle.py -> build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests copying statsmodels/miscmodels/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests copying statsmodels/miscmodels/tests/test_poisson.py -> build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests copying statsmodels/miscmodels/tests/test_tmodel.py -> build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests copying statsmodels/miscmodels/tests/test_ordinal_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests/results copying statsmodels/miscmodels/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests/results copying statsmodels/miscmodels/tests/results/results_ordinal_model.py -> build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/gam/gam_cross_validation copying statsmodels/gam/gam_cross_validation/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/gam_cross_validation copying statsmodels/gam/gam_cross_validation/cross_validators.py -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/gam_cross_validation copying statsmodels/gam/gam_cross_validation/gam_cross_validation.py -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/gam_cross_validation creating build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests copying statsmodels/gam/tests/test_smooth_basis.py -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests copying statsmodels/gam/tests/test_penalized.py -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests copying statsmodels/gam/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests copying statsmodels/gam/tests/test_gam.py -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results copying statsmodels/gam/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results copying statsmodels/gam/tests/results/results_mpg_bs.py -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results copying statsmodels/gam/tests/results/results_pls.py -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results copying statsmodels/gam/tests/results/results_mpg_bs_poisson.py -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/othermod/tests copying statsmodels/othermod/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/othermod/tests copying statsmodels/othermod/tests/test_beta.py -> build/lib.linux-x86_64-cpython-313/statsmodels/othermod/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/othermod/tests/results copying statsmodels/othermod/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/othermod/tests/results copying statsmodels/othermod/tests/results/results_betareg.py -> build/lib.linux-x86_64-cpython-313/statsmodels/othermod/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests copying statsmodels/duration/tests/test_phreg.py -> build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests copying statsmodels/duration/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests copying statsmodels/duration/tests/test_survfunc.py -> build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results copying statsmodels/duration/tests/results/survival_r_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results copying statsmodels/duration/tests/results/phreg_gentests.py -> build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results copying statsmodels/duration/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results copying statsmodels/duration/tests/results/survival_enet_r_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests copying statsmodels/nonparametric/tests/test_bandwidths.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests copying statsmodels/nonparametric/tests/test_kernels.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests copying statsmodels/nonparametric/tests/test_asymmetric.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests copying statsmodels/nonparametric/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests copying statsmodels/nonparametric/tests/test_kde.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests copying statsmodels/nonparametric/tests/test_kernel_regression.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests copying statsmodels/nonparametric/tests/test_lowess.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests copying statsmodels/nonparametric/tests/test_kernel_density.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results copying statsmodels/nonparametric/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests copying statsmodels/emplike/tests/test_descriptive.py -> build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests copying statsmodels/emplike/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests copying statsmodels/emplike/tests/test_anova.py -> build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests copying statsmodels/emplike/tests/test_regression.py -> build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests copying statsmodels/emplike/tests/test_aft.py -> build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests copying statsmodels/emplike/tests/test_origin.py -> build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests/results copying statsmodels/emplike/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests/results copying statsmodels/emplike/tests/results/el_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/china_smoking copying statsmodels/datasets/china_smoking/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/china_smoking copying statsmodels/datasets/china_smoking/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/china_smoking creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/sunspots copying statsmodels/datasets/sunspots/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/sunspots copying statsmodels/datasets/sunspots/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/sunspots creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/star98 copying statsmodels/datasets/star98/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/star98 copying statsmodels/datasets/star98/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/star98 creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/committee copying statsmodels/datasets/committee/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/committee copying statsmodels/datasets/committee/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/committee creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/elnino copying statsmodels/datasets/elnino/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/elnino copying statsmodels/datasets/elnino/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/elnino creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/copper copying statsmodels/datasets/copper/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/copper copying statsmodels/datasets/copper/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/copper creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/strikes copying statsmodels/datasets/strikes/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/strikes copying statsmodels/datasets/strikes/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/strikes creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/heart copying statsmodels/datasets/heart/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/heart copying statsmodels/datasets/heart/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/heart creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/modechoice copying statsmodels/datasets/modechoice/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/modechoice copying statsmodels/datasets/modechoice/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/modechoice creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/spector copying statsmodels/datasets/spector/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/spector copying statsmodels/datasets/spector/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/spector creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/randhie copying statsmodels/datasets/randhie/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/randhie copying statsmodels/datasets/randhie/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/randhie creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/interest_inflation copying statsmodels/datasets/interest_inflation/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/interest_inflation copying statsmodels/datasets/interest_inflation/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/interest_inflation creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/anes96 copying statsmodels/datasets/anes96/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/anes96 copying statsmodels/datasets/anes96/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/anes96 creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/danish_data copying statsmodels/datasets/danish_data/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/danish_data copying statsmodels/datasets/danish_data/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/danish_data creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/nile copying statsmodels/datasets/nile/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/nile copying statsmodels/datasets/nile/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/nile creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/co2 copying statsmodels/datasets/co2/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/co2 copying statsmodels/datasets/co2/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/co2 creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/longley copying statsmodels/datasets/longley/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/longley copying statsmodels/datasets/longley/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/longley creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/fair copying statsmodels/datasets/fair/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/fair copying statsmodels/datasets/fair/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/fair creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/statecrime copying statsmodels/datasets/statecrime/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/statecrime copying statsmodels/datasets/statecrime/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/statecrime creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/stackloss copying statsmodels/datasets/stackloss/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/stackloss copying statsmodels/datasets/stackloss/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/stackloss creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/engel copying statsmodels/datasets/engel/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/engel copying statsmodels/datasets/engel/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/engel creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/grunfeld copying statsmodels/datasets/grunfeld/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/grunfeld copying statsmodels/datasets/grunfeld/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/grunfeld creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/cpunish copying statsmodels/datasets/cpunish/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/cpunish copying statsmodels/datasets/cpunish/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/cpunish creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/fertility copying statsmodels/datasets/fertility/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/fertility copying statsmodels/datasets/fertility/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/fertility creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/cancer copying statsmodels/datasets/cancer/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/cancer copying statsmodels/datasets/cancer/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/cancer creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/elec_equip copying statsmodels/datasets/elec_equip/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/elec_equip copying statsmodels/datasets/elec_equip/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/elec_equip creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/ccard copying statsmodels/datasets/ccard/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/ccard copying statsmodels/datasets/ccard/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/ccard creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/macrodata copying statsmodels/datasets/macrodata/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/macrodata copying statsmodels/datasets/macrodata/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/macrodata creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/tests copying statsmodels/datasets/tests/test_data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/tests copying statsmodels/datasets/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/tests copying statsmodels/datasets/tests/test_utils.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/datasets/scotland copying statsmodels/datasets/scotland/data.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/scotland copying statsmodels/datasets/scotland/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/scotland creating build/lib.linux-x86_64-cpython-313/statsmodels/imputation/tests copying statsmodels/imputation/tests/test_ros.py -> build/lib.linux-x86_64-cpython-313/statsmodels/imputation/tests copying statsmodels/imputation/tests/test_bayes_mi.py -> build/lib.linux-x86_64-cpython-313/statsmodels/imputation/tests copying statsmodels/imputation/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/imputation/tests copying statsmodels/imputation/tests/test_mice.py -> build/lib.linux-x86_64-cpython-313/statsmodels/imputation/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests copying statsmodels/graphics/tests/test_correlation.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests copying statsmodels/graphics/tests/test_agreement.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests copying statsmodels/graphics/tests/test_tsaplots.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests copying statsmodels/graphics/tests/test_gofplots.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests copying statsmodels/graphics/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests copying statsmodels/graphics/tests/test_factorplots.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests copying statsmodels/graphics/tests/test_regressionplots.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests copying statsmodels/graphics/tests/test_boxplots.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests copying statsmodels/graphics/tests/test_functional.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests copying statsmodels/graphics/tests/test_mosaicplot.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests copying statsmodels/graphics/tests/test_dotplot.py -> build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/mcevaluate copying statsmodels/sandbox/mcevaluate/arma.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/mcevaluate copying statsmodels/sandbox/mcevaluate/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/mcevaluate creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats copying statsmodels/sandbox/stats/runs.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats copying statsmodels/sandbox/stats/multicomp.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats copying statsmodels/sandbox/stats/stats_mstats_short.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats copying statsmodels/sandbox/stats/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats copying statsmodels/sandbox/stats/diagnostic.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats copying statsmodels/sandbox/stats/stats_dhuard.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats copying statsmodels/sandbox/stats/contrast_tools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats copying statsmodels/sandbox/stats/ex_newtests.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa copying statsmodels/sandbox/tsa/try_arma_more.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa copying statsmodels/sandbox/tsa/try_fi.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa copying statsmodels/sandbox/tsa/example_arma.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa copying statsmodels/sandbox/tsa/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa copying statsmodels/sandbox/tsa/diffusion.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa copying statsmodels/sandbox/tsa/diffusion2.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa copying statsmodels/sandbox/tsa/try_var_convolve.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa copying statsmodels/sandbox/tsa/fftarma.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa copying statsmodels/sandbox/tsa/varma.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa copying statsmodels/sandbox/tsa/movstat.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression copying statsmodels/sandbox/regression/predstd.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression copying statsmodels/sandbox/regression/onewaygls.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression copying statsmodels/sandbox/regression/treewalkerclass.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression copying statsmodels/sandbox/regression/gmm.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression copying statsmodels/sandbox/regression/kernridgeregress_class.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression copying statsmodels/sandbox/regression/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression copying statsmodels/sandbox/regression/try_ols_anova.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression copying statsmodels/sandbox/regression/tools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression copying statsmodels/sandbox/regression/example_kernridge.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression copying statsmodels/sandbox/regression/runmnl.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression copying statsmodels/sandbox/regression/penalized.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression copying statsmodels/sandbox/regression/ols_anova_original.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression copying statsmodels/sandbox/regression/ar_panel.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression copying statsmodels/sandbox/regression/sympy_diff.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression copying statsmodels/sandbox/regression/try_treewalker.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression copying statsmodels/sandbox/regression/anova_nistcertified.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression copying statsmodels/sandbox/regression/try_catdata.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tools copying statsmodels/sandbox/tools/cross_val.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tools copying statsmodels/sandbox/tools/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tools copying statsmodels/sandbox/tools/mctools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tools copying statsmodels/sandbox/tools/tools_pca.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tools copying statsmodels/sandbox/tools/try_mctools.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tools creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions copying statsmodels/sandbox/distributions/try_max.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions copying statsmodels/sandbox/distributions/otherdist.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions copying statsmodels/sandbox/distributions/multivariate.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions copying statsmodels/sandbox/distributions/mv_normal.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions copying statsmodels/sandbox/distributions/try_pot.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions copying statsmodels/sandbox/distributions/transformed.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions copying statsmodels/sandbox/distributions/genpareto.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions copying statsmodels/sandbox/distributions/estimators.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions copying statsmodels/sandbox/distributions/quantize.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions copying statsmodels/sandbox/distributions/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions copying statsmodels/sandbox/distributions/sppatch.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions copying statsmodels/sandbox/distributions/gof_new.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions copying statsmodels/sandbox/distributions/transform_functions.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions copying statsmodels/sandbox/distributions/extras.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions copying statsmodels/sandbox/distributions/mv_measures.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/archive copying statsmodels/sandbox/archive/linalg_decomp_1.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/archive copying statsmodels/sandbox/archive/tsa.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/archive copying statsmodels/sandbox/archive/linalg_covmat.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/archive copying statsmodels/sandbox/archive/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/archive creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/datarich copying statsmodels/sandbox/datarich/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/datarich copying statsmodels/sandbox/datarich/factormodels.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/datarich creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric copying statsmodels/sandbox/nonparametric/smoothers.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric copying statsmodels/sandbox/nonparametric/dgp_examples.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric copying statsmodels/sandbox/nonparametric/testdata.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric copying statsmodels/sandbox/nonparametric/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric copying statsmodels/sandbox/nonparametric/densityorthopoly.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric copying statsmodels/sandbox/nonparametric/kernel_extras.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric copying statsmodels/sandbox/nonparametric/kdecovclass.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric copying statsmodels/sandbox/nonparametric/kernels.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric copying statsmodels/sandbox/nonparametric/kde2.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel copying statsmodels/sandbox/panel/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel copying statsmodels/sandbox/panel/sandwich_covariance_generic.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel copying statsmodels/sandbox/panel/panel_short.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel copying statsmodels/sandbox/panel/mixed.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel copying statsmodels/sandbox/panel/panelmod.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel copying statsmodels/sandbox/panel/correlation_structures.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel copying statsmodels/sandbox/panel/random_panel.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tests copying statsmodels/sandbox/tests/maketests_mlabwrap.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tests copying statsmodels/sandbox/tests/savervs.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tests copying statsmodels/sandbox/tests/test_predict_functional.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tests copying statsmodels/sandbox/tests/test_pca.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tests copying statsmodels/sandbox/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tests copying statsmodels/sandbox/tests/test_gam.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats/tests copying statsmodels/sandbox/stats/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats/tests copying statsmodels/sandbox/stats/tests/test_runs.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats/tests copying statsmodels/sandbox/stats/tests/test_multicomp.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests copying statsmodels/sandbox/regression/tests/test_gmm_poisson.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests copying statsmodels/sandbox/regression/tests/results_gmm_griliches_iter.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests copying statsmodels/sandbox/regression/tests/test_gmm.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests copying statsmodels/sandbox/regression/tests/results_gmm_poisson.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests copying statsmodels/sandbox/regression/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests copying statsmodels/sandbox/regression/tests/results_ivreg2_griliches.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests copying statsmodels/sandbox/regression/tests/results_gmm_griliches.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/examples copying statsmodels/sandbox/distributions/examples/ex_mvelliptical.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/examples copying statsmodels/sandbox/distributions/examples/ex_gof.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/examples copying statsmodels/sandbox/distributions/examples/ex_fitfr.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/examples copying statsmodels/sandbox/distributions/examples/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/examples copying statsmodels/sandbox/distributions/examples/ex_extras.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/examples copying statsmodels/sandbox/distributions/examples/matchdist.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/examples copying statsmodels/sandbox/distributions/examples/ex_transf2.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/examples creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests copying statsmodels/sandbox/distributions/tests/test_norm_expan.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests copying statsmodels/sandbox/distributions/tests/test_multivariate.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests copying statsmodels/sandbox/distributions/tests/check_moments.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests copying statsmodels/sandbox/distributions/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests copying statsmodels/sandbox/distributions/tests/test_extras.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests copying statsmodels/sandbox/distributions/tests/test_gof_new.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests copying statsmodels/sandbox/distributions/tests/_est_fit.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests copying statsmodels/sandbox/distributions/tests/test_transf.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests copying statsmodels/sandbox/distributions/tests/distparams.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/tests copying statsmodels/sandbox/nonparametric/tests/ex_smoothers.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/tests copying statsmodels/sandbox/nonparametric/tests/test_smoothers.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/tests copying statsmodels/sandbox/nonparametric/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/tests copying statsmodels/sandbox/nonparametric/tests/ex_gam_new.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/tests copying statsmodels/sandbox/nonparametric/tests/ex_gam_am_new.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/tests copying statsmodels/sandbox/nonparametric/tests/test_kernel_extras.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel/tests copying statsmodels/sandbox/panel/tests/test_random_panel.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel/tests copying statsmodels/sandbox/panel/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests copying statsmodels/robust/tests/test_scale.py -> build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests copying statsmodels/robust/tests/test_mquantiles.py -> build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests copying statsmodels/robust/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests copying statsmodels/robust/tests/test_norms.py -> build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests copying statsmodels/robust/tests/test_rlm.py -> build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests/results copying statsmodels/robust/tests/results/results_rlm.py -> build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests/results copying statsmodels/robust/tests/results/results_norms.py -> build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests/results copying statsmodels/robust/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/genmod/families copying statsmodels/genmod/families/family.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/families copying statsmodels/genmod/families/varfuncs.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/families copying statsmodels/genmod/families/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/families copying statsmodels/genmod/families/links.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/families creating build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests copying statsmodels/genmod/tests/gee_poisson_simulation_check.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests copying statsmodels/genmod/tests/test_score_test.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests copying statsmodels/genmod/tests/test_qif.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests copying statsmodels/genmod/tests/test_constrained.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests copying statsmodels/genmod/tests/test_bayes_mixed_glm.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests copying statsmodels/genmod/tests/test_glm.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests copying statsmodels/genmod/tests/gee_simulation_check.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests copying statsmodels/genmod/tests/test_gee.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests copying statsmodels/genmod/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests copying statsmodels/genmod/tests/test_gee_glm.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests copying statsmodels/genmod/tests/gee_gaussian_simulation_check.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests copying statsmodels/genmod/tests/gee_categorical_simulation_check.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests copying statsmodels/genmod/tests/test_glm_weights.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/genmod/families/tests copying statsmodels/genmod/families/tests/test_link.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/families/tests copying statsmodels/genmod/families/tests/test_family.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/families/tests copying statsmodels/genmod/families/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/families/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/res_R_var_weight.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/results_glm.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/gee_generate_tests.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/glmnet_r_results.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/results_glm_poisson_weights.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/glm_test_resids.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/elastic_net_generate_tests.py -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/factor_rotation copying statsmodels/multivariate/factor_rotation/_analytic_rotation.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/factor_rotation copying statsmodels/multivariate/factor_rotation/_wrappers.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/factor_rotation copying statsmodels/multivariate/factor_rotation/_gpa_rotation.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/factor_rotation copying statsmodels/multivariate/factor_rotation/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/factor_rotation creating build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests copying statsmodels/multivariate/tests/test_multivariate_ols.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests copying statsmodels/multivariate/tests/test_manova.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests copying statsmodels/multivariate/tests/test_pca.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests copying statsmodels/multivariate/tests/test_cancorr.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests copying statsmodels/multivariate/tests/test_factor.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests copying statsmodels/multivariate/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests copying statsmodels/multivariate/tests/test_ml_factor.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/factor_rotation/tests copying statsmodels/multivariate/factor_rotation/tests/test_rotation.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/factor_rotation/tests copying statsmodels/multivariate/factor_rotation/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/factor_rotation/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests/results copying statsmodels/multivariate/tests/results/datamlw.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests/results copying statsmodels/multivariate/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests/results creating build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests copying statsmodels/iolib/tests/test_table.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests copying statsmodels/iolib/tests/test_table_econpy.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests copying statsmodels/iolib/tests/test_pickle.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests copying statsmodels/iolib/tests/test_summary2.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests copying statsmodels/iolib/tests/test_summary_old.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests copying statsmodels/iolib/tests/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests copying statsmodels/iolib/tests/test_summary.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests creating build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests/results copying statsmodels/iolib/tests/results/__init__.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests/results copying statsmodels/iolib/tests/results/macrodata.py -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests/results copying statsmodels/LICENSE.txt -> build/lib.linux-x86_64-cpython-313/statsmodels copying statsmodels/setup.cfg -> build/lib.linux-x86_64-cpython-313/statsmodels copying statsmodels/treatment/tests/results/cataneo2.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/treatment/tests/results copying statsmodels/stats/libqsturng/CH.r -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng copying statsmodels/stats/libqsturng/LICENSE.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng copying statsmodels/stats/tests/test_data.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests copying statsmodels/stats/libqsturng/tests/bootleg.dat -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng/tests copying statsmodels/stats/tests/results/framing.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/bootleg.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/influence_measures_bool_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/wspec2.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/influence_measures_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/wspec1.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/binary_constrict.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/results_influence_logit.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/wspec3.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/wspec4.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/contingency_table_r_results.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/influence_lsdiag_R.json -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/stats/tests/results/data.dat -> build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results copying statsmodels/tsa/statespace/tests/results/results_exact_initial_var1_mixed_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_smoothing_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_wpi1_ar3_matlab_ssm.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/cfa_tvpvar_posterior_mean.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_simulation_smoothing3.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_exact_initial_local_linear_trend_missing_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_simulation_smoothing1.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_realgdpar_stata.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_simulation_smoothing0.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_wpi1_ar3_stata.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_varmax_stata.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_var_R_output.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/cfa_tvpvar_state_variates.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_intercepts_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_wpi1_missing_ar3_matlab_ssm.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_exact_initial_common_level_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_exact_initial_local_level_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_exact_initial_var1_measurement_error_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/cfa_tvpvar_Omega_22.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_simulation_smoothing4.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/cfa_tvpvar_v10.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_simulation_smoothing5.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/cfa_tvpvar_beta.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/cfa_tvpvar_invP.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/cfa_tvpvar_Si0.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_sarimax_coverage.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_exact_initial_dfm_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_smoothing3_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/exponential_smoothing_predict.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_exact_initial_common_level_restricted_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/exponential_smoothing_params.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_simulation_smoothing2.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/exponential_smoothing_states.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/cfa_tvpvar_vi0.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_var_stata.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_smoothing_generalobscov_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/clark1989.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_exact_initial_var1_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_simulation_smoothing3_variates.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_clark1989_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/cfa_tvpvar_Omega_11.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_exact_initial_var1_missing_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_simulation_smoothing6.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_smoothing2_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/cfa_tvpvar_S10.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_exact_initial_local_linear_trend_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/results_dynamic_factor_stata.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/manufac.dta -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/sm-0.9-sarimax.pkl -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_news_222.mat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_news_112.mat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_221.mat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_222.mat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_111.mat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_22F.mat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_blocks_222.mat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_112.mat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_blocks_221.mat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_blocks_112.mat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_news_blocks_222.mat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_blocks_111.mat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_11F.mat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_news_blocks_112.mat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data/US/2016-06-29.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data/US copying statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data/US/2016-07-29.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data/US copying statsmodels/tsa/holtwinters/tests/results/housing-data.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/tests/results copying statsmodels/tsa/stl/tests/results/stl_co2.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests/results copying statsmodels/tsa/stl/tests/results/mstl_elec_vic.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests/results copying statsmodels/tsa/stl/tests/results/mstl_test_results.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests/results copying statsmodels/tsa/stl/tests/results/stl_test_results.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests/results copying statsmodels/tsa/regime_switching/tests/results/results_predict_rgnp.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests/results copying statsmodels/tsa/regime_switching/tests/results/results_predict_fedfunds.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests/results copying statsmodels/tsa/regime_switching/tests/results/mar_filardo.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests/results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_lagorder.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_granger_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realcons_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_Sigmau.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_granger_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_fc5.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_fc5.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_ir.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_diag.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_ir.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_granger_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_lagorder.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_inst_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_diag.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realcons.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_diag.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realcons_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realcons_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_inst_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_lagorder.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realgdp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_diag.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_inst_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realgdp_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_ir.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_ir.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_Sigmau.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realgdp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_lagorder.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_Sigmau.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_inst_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_fc5.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_lagorder.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_inst_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_diag.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_ir.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_fc5.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_inst_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realcons_realgdp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_ir.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_lagorder.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realgdp_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_fc5.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_fc5.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_ir.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_Sigmau.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_inst_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_lagorder.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_Sigmau.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_Sigmau.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_diag.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_fc5.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_Sigmau.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_granger_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_diag.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_diag.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_granger_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_lagorder.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_fc5.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_lagorder.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_granger_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_lagorder.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_ir.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_diag.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_Sigmau.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realgdp_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_granger_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_granger_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_Sigmau.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_lagorder.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realcons.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_Sigmau.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_ir.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realcons.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_lagorder.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realcons_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_diag.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realgdp_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_Sigmau.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_fc5.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_inst_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_Sigmau.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realgdp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realgdp_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_ir.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_lagorder.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_ir.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_fc5.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_granger_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_inst_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_granger_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_ir.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_diag.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realgdp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_granger_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_fc5.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_granger_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_ir.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_fc5.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realcons_realgdp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_inst_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_granger_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_granger_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_lagorder.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_inst_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realcons.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realcons_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_granger_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realcons_realgdp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_diag.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_diag.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realgdp_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_Sigmau.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_lagorder.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_Sigmau.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_inst_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_diag.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_inst_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_granger_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_inst_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realcons_realgdp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_fc5.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_granger_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_ir.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_inst_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_Sigmau.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_fc5.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_diag.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_granger_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realcons_realinv.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_lagorder.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realcons.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_granger_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_granger_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_inst_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realcons_realgdp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_inst_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_ir.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_Sigmau.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_fc5.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_diag.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_inst_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realgdp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_ir.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_inst_causality_dp_r.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realcons_realgdp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_fc5.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realgdp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realcons.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_inst_causality_r_dp.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results copying statsmodels/tsa/vector_ar/tests/results/vars_results.npz -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results copying statsmodels/tsa/vector_ar/tests/results/e6.dat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results copying statsmodels/tsa/vector_ar/tests/results/e5.dat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results copying statsmodels/tsa/vector_ar/tests/results/e3.dat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results copying statsmodels/tsa/vector_ar/tests/results/e2.dat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results copying statsmodels/tsa/vector_ar/tests/results/e1.dat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results copying statsmodels/tsa/vector_ar/tests/results/e4.dat -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results copying statsmodels/tsa/vector_ar/tests/Matlab_results/test_coint.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/Matlab_results copying statsmodels/tsa/tests/results/yhat_exact_c.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/yhat_css_nc.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/y_arma_data.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/rgnpq.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/rgnp.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/ARMLEConstantPredict.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/results_ar_forecast_mle_dynamic.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/AROLSNoConstantPredict.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/yhat_css_c.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/results_arima_exog_forecasts_css.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/gnpdef.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/resids_exact_nc.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/results_arima_forecasts_all_mle_diff.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/arima111_forecasts.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/resids_exact_c.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/AROLSConstantPredict.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/resids_css_nc.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/bds_data.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/yhat_exact_nc.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/bds_results.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/results_arima_exog_forecasts_mle.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/results_arma_forecasts.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/results_arima_forecasts_all_css_diff.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/resids_css_c.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/results_arima_forecasts_all_css.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/arima212_forecast.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/stkprc.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/rand10000.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/results_arima_forecasts.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/results_arima_forecasts_all_mle.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/results_ccf.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/results_corrgram.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/lutkepohl2.dta -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/fit_ets_results_seasonal.json -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/fit_ets_results_nonseasonal.json -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/tsa/tests/results/fit_ets_results.json -> build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results copying statsmodels/regression/tests/results/lme06.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/lme04.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/results_rls_R.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/lme09.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/lme07.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/lme10.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/lme05.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/lme01.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/lme02.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/results_rls_stata.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/lme00.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/dietox.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/lme08.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/lme03.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/lme11.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/lasso_data.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/pastes.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/theil_textile_predict.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/regression/tests/results/leverage_influence_ols_nostars.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results copying statsmodels/discrete/tests/results/ships.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/poisson_resid.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/predict_prob_poisson.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/phat_mnlogit.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/nbinom_resids.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/sm3533.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/yhat_mnlogit.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/mnlogit_resid.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/yhat_poisson.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/discrete/tests/results/mn_logit_summary.txt -> build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results copying statsmodels/miscmodels/tests/results/ologit_ucla.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests/results copying statsmodels/gam/tests/results/cubic_cyclic_splines_from_mgcv.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results copying statsmodels/gam/tests/results/gam_PIRLS_results.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results copying statsmodels/gam/tests/results/prediction_from_mgcv.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results copying statsmodels/gam/tests/results/autos_exog.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results copying statsmodels/gam/tests/results/motorcycle.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results copying statsmodels/gam/tests/results/autos_predict.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results copying statsmodels/gam/tests/results/logit_gam_mgcv.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results copying statsmodels/gam/tests/results/autos.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results copying statsmodels/othermod/tests/results/foodexpenditure.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/othermod/tests/results copying statsmodels/othermod/tests/results/resid_methylation.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/othermod/tests/results copying statsmodels/othermod/tests/results/methylation-test.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/othermod/tests/results copying statsmodels/duration/tests/results/bmt.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results copying statsmodels/duration/tests/results/survival_data_50_2.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results copying statsmodels/duration/tests/results/bmt_results.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results copying statsmodels/duration/tests/results/survival_data_1000_10.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results copying statsmodels/duration/tests/results/survival_data_100_5.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results copying statsmodels/duration/tests/results/survival_data_50_1.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results copying statsmodels/duration/tests/results/survival_data_20_1.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results copying statsmodels/nonparametric/tests/results/results_kcde.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results copying statsmodels/nonparametric/tests/results/test_lowess_delta.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results copying statsmodels/nonparametric/tests/results/test_lowess_frac.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results copying statsmodels/nonparametric/tests/results/results_kde_fft.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results copying statsmodels/nonparametric/tests/results/results_kde_univ_weights.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results copying statsmodels/nonparametric/tests/results/test_lowess_simple.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results copying statsmodels/nonparametric/tests/results/test_lowess_iter.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results copying statsmodels/nonparametric/tests/results/results_kde_weights.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results copying statsmodels/nonparametric/tests/results/results_kernel_regression.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results copying statsmodels/nonparametric/tests/results/results_kde.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results copying statsmodels/datasets/china_smoking/china_smoking.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/china_smoking copying statsmodels/datasets/sunspots/sunspots.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/sunspots copying statsmodels/datasets/star98/star98.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/star98 copying statsmodels/datasets/committee/committee.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/committee copying statsmodels/datasets/elnino/elnino.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/elnino copying statsmodels/datasets/copper/copper.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/copper copying statsmodels/datasets/strikes/strikes.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/strikes copying statsmodels/datasets/heart/heart.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/heart copying statsmodels/datasets/modechoice/modechoice.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/modechoice copying statsmodels/datasets/spector/spector.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/spector copying statsmodels/datasets/randhie/randhie.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/randhie copying statsmodels/datasets/interest_inflation/E6.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/interest_inflation copying statsmodels/datasets/interest_inflation/E6_jmulti.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/interest_inflation copying statsmodels/datasets/anes96/anes96.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/anes96 copying statsmodels/datasets/danish_data/data.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/danish_data copying statsmodels/datasets/nile/nile.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/nile copying statsmodels/datasets/co2/co2.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/co2 copying statsmodels/datasets/longley/longley.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/longley copying statsmodels/datasets/fair/fair.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/fair copying statsmodels/datasets/fair/fair_pt.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/fair copying statsmodels/datasets/statecrime/statecrime.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/statecrime copying statsmodels/datasets/stackloss/stackloss.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/stackloss copying statsmodels/datasets/engel/engel.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/engel copying statsmodels/datasets/grunfeld/grunfeld.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/grunfeld copying statsmodels/datasets/cpunish/cpunish.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/cpunish copying statsmodels/datasets/fertility/fertility.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/fertility copying statsmodels/datasets/cancer/cancer.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/cancer copying statsmodels/datasets/elec_equip/elec_equip.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/elec_equip copying statsmodels/datasets/ccard/ccard.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/ccard copying statsmodels/datasets/macrodata/macrodata.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/macrodata copying statsmodels/datasets/macrodata/macrodata.dta -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/macrodata copying statsmodels/datasets/scotland/scotvote.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/datasets/scotland copying statsmodels/sandbox/regression/tests/griliches76.dta -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests copying statsmodels/sandbox/regression/tests/racd10data_with_transformed.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests copying statsmodels/genmod/tests/results/enet_binomial.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/stata_lbw_glm.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/gee_nominal_1.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/gee_ordinal_1.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/gee_linear_1.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/epil.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/gee_nested_linear_1.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/medparlogresids.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/stata_cancer_glm.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/iris.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/gee_logistic_1.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/enet_poisson.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/igaussident_resids.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/gee_poisson_1.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/inv_gaussian.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/stata_medpar1_glm.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/genmod/tests/results/results_tweedie_aweights_nonrobust.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results copying statsmodels/multivariate/tests/results/factor_data.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests/results copying statsmodels/multivariate/tests/results/factors_stata.csv -> build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests/results copying statsmodels/iolib/tests/results/time_series_examples.dta -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests/results copying statsmodels/iolib/tests/results/data_missing.dta -> build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests/results running build_ext building 'statsmodels.tsa.stl._stl' extension creating build/temp.linux-x86_64-cpython-313/statsmodels/tsa/stl x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/stl/_stl.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/stl/_stl.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/stl/_stl.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/_stl.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.holtwinters._exponential_smoothers' extension creating build/temp.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/holtwinters/_exponential_smoothers.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/_exponential_smoothers.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/_exponential_smoothers.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/_exponential_smoothers.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.exponential_smoothing._ets_smooth' extension creating build/temp.linux-x86_64-cpython-313/statsmodels/tsa/exponential_smoothing x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/exponential_smoothing/_ets_smooth.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/exponential_smoothing/_ets_smooth.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/exponential_smoothing/_ets_smooth.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/exponential_smoothing/_ets_smooth.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa._innovations' extension x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/_innovations.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/_innovations.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/_innovations.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/_innovations.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.regime_switching._hamilton_filter' extension creating build/temp.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/regime_switching/_hamilton_filter.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/_hamilton_filter.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/_hamilton_filter.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/_hamilton_filter.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.regime_switching._kim_smoother' extension x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/regime_switching/_kim_smoother.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/_kim_smoother.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/_kim_smoother.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/_kim_smoother.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.innovations._arma_innovations' extension creating build/temp.linux-x86_64-cpython-313/statsmodels/tsa/innovations x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/innovations/_arma_innovations.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/innovations/_arma_innovations.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/innovations/_arma_innovations.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/innovations/_arma_innovations.cpython-313-x86_64-linux-gnu.so building 'statsmodels.nonparametric.linbin' extension creating build/temp.linux-x86_64-cpython-313/statsmodels/nonparametric x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/nonparametric/linbin.c -o build/temp.linux-x86_64-cpython-313/statsmodels/nonparametric/linbin.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/nonparametric/linbin.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/linbin.cpython-313-x86_64-linux-gnu.so building 'statsmodels.robust._qn' extension creating build/temp.linux-x86_64-cpython-313/statsmodels/robust x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/robust/_qn.c -o build/temp.linux-x86_64-cpython-313/statsmodels/robust/_qn.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/robust/_qn.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/robust/_qn.cpython-313-x86_64-linux-gnu.so building 'statsmodels.nonparametric._smoothers_lowess' extension x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/nonparametric/_smoothers_lowess.c -o build/temp.linux-x86_64-cpython-313/statsmodels/nonparametric/_smoothers_lowess.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/nonparametric/_smoothers_lowess.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/_smoothers_lowess.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.statespace._initialization' extension creating build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -Istatsmodels/src -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/statespace/_initialization.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_initialization.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_initialization.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_initialization.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.statespace._representation' extension x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -Istatsmodels/src -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/statespace/_representation.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_representation.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_representation.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_representation.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.statespace._kalman_filter' extension x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -Istatsmodels/src -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/statespace/_kalman_filter.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_kalman_filter.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_kalman_filter.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_kalman_filter.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.statespace._filters._conventional' extension creating build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -Istatsmodels/src -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/statespace/_filters/_conventional.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters/_conventional.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters/_conventional.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters/_conventional.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.statespace._filters._inversions' extension x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -Istatsmodels/src -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/statespace/_filters/_inversions.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters/_inversions.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters/_inversions.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters/_inversions.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.statespace._filters._univariate' extension x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -Istatsmodels/src -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/statespace/_filters/_univariate.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters/_univariate.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters/_univariate.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters/_univariate.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.statespace._filters._univariate_diffuse' extension x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -Istatsmodels/src -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/statespace/_filters/_univariate_diffuse.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters/_univariate_diffuse.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters/_univariate_diffuse.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters/_univariate_diffuse.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.statespace._kalman_smoother' extension x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -Istatsmodels/src -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/statespace/_kalman_smoother.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_kalman_smoother.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_kalman_smoother.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_kalman_smoother.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.statespace._smoothers._alternative' extension creating build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -Istatsmodels/src -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/statespace/_smoothers/_alternative.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_alternative.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_alternative.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_alternative.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.statespace._smoothers._classical' extension x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -Istatsmodels/src -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/statespace/_smoothers/_classical.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_classical.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_classical.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_classical.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.statespace._smoothers._conventional' extension x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -Istatsmodels/src -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/statespace/_smoothers/_conventional.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_conventional.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_conventional.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_conventional.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.statespace._smoothers._univariate' extension x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -Istatsmodels/src -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/statespace/_smoothers/_univariate.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_univariate.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_univariate.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_univariate.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.statespace._smoothers._univariate_diffuse' extension x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -Istatsmodels/src -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.statespace._simulation_smoother' extension x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -Istatsmodels/src -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/statespace/_simulation_smoother.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_simulation_smoother.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_simulation_smoother.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_simulation_smoother.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.statespace._cfa_simulation_smoother' extension x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -Istatsmodels/src -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/statespace/_cfa_simulation_smoother.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_cfa_simulation_smoother.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_cfa_simulation_smoother.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_cfa_simulation_smoother.cpython-313-x86_64-linux-gnu.so building 'statsmodels.tsa.statespace._tools' extension x86_64-linux-gnu-gcc -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -DCYTHON_TRACE_NOGIL=0 -DNPY_NO_DEPRECATED_API=NPY_1_7_API_VERSION -Istatsmodels/src -I/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include -I/usr/include/python3.13 -c statsmodels/tsa/statespace/_tools.c -o build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_tools.o x86_64-linux-gnu-gcc -shared -Wl,-O1 -Wl,-Bsymbolic-functions -Wl,-z,relro -g -fwrapv -O2 -Wl,-z,relro -Wl,-z,now -g -O2 -Werror=implicit-function-declaration -ffile-prefix-map=/build/reproducible-path/statsmodels-0.14.5+dfsg=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -Wdate-time -D_FORTIFY_SOURCE=2 build/temp.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_tools.o -L/usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/../lib -L/usr/lib/x86_64-linux-gnu -lnpymath -o build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_tools.cpython-313-x86_64-linux-gnu.so installing to build/bdist.linux-x86_64/wheel running install running install_lib creating build/bdist.linux-x86_64/wheel creating build/bdist.linux-x86_64/wheel/statsmodels creating build/bdist.linux-x86_64/wheel/statsmodels/treatment copying build/lib.linux-x86_64-cpython-313/statsmodels/treatment/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/treatment copying build/lib.linux-x86_64-cpython-313/statsmodels/treatment/treatment_effects.py -> build/bdist.linux-x86_64/wheel/./statsmodels/treatment creating build/bdist.linux-x86_64/wheel/statsmodels/treatment/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/treatment/tests/test_teffects.py -> build/bdist.linux-x86_64/wheel/./statsmodels/treatment/tests creating build/bdist.linux-x86_64/wheel/statsmodels/treatment/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/treatment/tests/results/cataneo2.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/treatment/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/treatment/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/treatment/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/treatment/tests/results/results_teffects.py -> build/bdist.linux-x86_64/wheel/./statsmodels/treatment/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/treatment/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/treatment/tests creating build/bdist.linux-x86_64/wheel/statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/gof.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/moment_helpers.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/anova.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/rates.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/contrast.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/sandwich_covariance.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/_lilliefors.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/power.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/multivariate.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/regularized_covariance.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/contingency_tables.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/inter_rater.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/_inference_tools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/robust_compare.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/multicomp.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/mediation.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/weightstats.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/oneway.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/_delta_method.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/descriptivestats.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/oaxaca.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/outliers_influence.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats creating build/bdist.linux-x86_64/wheel/statsmodels/stats/libqsturng copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng/make_tbls.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/libqsturng copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng/LICENSE.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/libqsturng copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/libqsturng copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng/CH.r -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/libqsturng copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng/qsturng_.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/libqsturng creating build/bdist.linux-x86_64/wheel/statsmodels/stats/libqsturng/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/libqsturng/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng/tests/bootleg.dat -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/libqsturng/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/libqsturng/tests/test_qsturng.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/libqsturng/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/proportion.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/correlation_tools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/effect_size.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/_adnorm.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/meta_analysis.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/diagnostic.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/stattools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/multivariate_tools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/_knockoff.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/base.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/nonparametric.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/multitest.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/_lilliefors_critical_values.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/knockoff_regeffects.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/_diagnostic_other.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/diagnostic_gen.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tabledist.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/dist_dependence_measures.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats creating build/bdist.linux-x86_64/wheel/statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_power.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_multi.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_anova_rm.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_correlation.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_statstools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_base.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_rates_poisson.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_corrpsd.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_lilliefors.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_mediation.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_diagnostic.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_oaxaca.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests creating build/bdist.linux-x86_64/wheel/statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/results_proportion.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/influence_lsdiag_R.json -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/data.dat -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/framing.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/results_meta.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/lilliefors_critical_value_simulation.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/bootleg.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/influence_measures_bool_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/wspec2.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/results_power.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/results_panelrobust.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/influence_measures_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/wspec1.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/binary_constrict.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/results_rates.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/results_influence_logit.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/wspec3.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/results_multinomial_proportions.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/wspec4.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/results/contingency_table_r_results.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_tost.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_multivariate.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_gof.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_influence.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_data.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_proportion.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_robust_compare.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_nonparametric.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_dist_dependant_measures.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_groups_sw.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_anova.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_meta.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_tabledist.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_sandwich.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_diagnostic_other.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_knockoff.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_outliers_influence.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_moment_helpers.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_contrast.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_contingency_tables.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_descriptivestats.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_deltacov.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_regularized_covariance.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_panel_robustcov.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_effectsize.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_oneway.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_qsturng.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_pairwise.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_inter_rater.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/stats/tests/test_weightstats.py -> build/bdist.linux-x86_64/wheel/./statsmodels/stats/tests creating build/bdist.linux-x86_64/wheel/statsmodels/src copying build/lib.linux-x86_64-cpython-313/statsmodels/src/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/src creating build/bdist.linux-x86_64/wheel/statsmodels/interface copying build/lib.linux-x86_64-cpython-313/statsmodels/interface/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/interface creating build/bdist.linux-x86_64/wheel/statsmodels/formula copying build/lib.linux-x86_64-cpython-313/statsmodels/formula/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/formula copying build/lib.linux-x86_64-cpython-313/statsmodels/formula/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/formula copying build/lib.linux-x86_64-cpython-313/statsmodels/formula/formulatools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/formula creating build/bdist.linux-x86_64/wheel/statsmodels/formula/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/formula/tests/test_formula.py -> build/bdist.linux-x86_64/wheel/./statsmodels/formula/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/formula/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/formula/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/_innovations.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/arima creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/arima/estimators copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/durbin_levinson.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/estimators copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/statespace.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/estimators copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/gls.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/estimators copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/yule_walker.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/estimators copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/estimators copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/burg.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/estimators copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/innovations.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/estimators copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/hannan_rissanen.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/estimators creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/arima/estimators/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/estimators/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/estimators/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/estimators/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/tests/test_innovations.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/estimators/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/tests/test_gls.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/estimators/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/tests/test_statespace.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/estimators/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/tests/test_burg.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/estimators/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/estimators/tests/test_yule_walker.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/estimators/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/tools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/specification.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/arima/datasets creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/arima/datasets/brockwell_davis_2002 creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/arima/datasets/brockwell_davis_2002/data copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/datasets/brockwell_davis_2002/data/lake.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/datasets/brockwell_davis_2002/data copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/datasets/brockwell_davis_2002/data/sbl.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/datasets/brockwell_davis_2002/data copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/datasets/brockwell_davis_2002/data/oshorts.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/datasets/brockwell_davis_2002/data copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/datasets/brockwell_davis_2002/data/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/datasets/brockwell_davis_2002/data copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/datasets/brockwell_davis_2002/data/dowj.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/datasets/brockwell_davis_2002/data copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/datasets/brockwell_davis_2002/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/datasets/brockwell_davis_2002 copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/datasets/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/datasets copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/params.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/arima/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/tests/test_params.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/tests/test_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/tests/test_specification.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima/tests/test_tools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/arima/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_simulation_smoother.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/kalman_smoother.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_tools.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_pykalman_smoother.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/initialization.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/kalman_filter.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_cfa_simulation_smoother.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/sarimax.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/structural.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/representation.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/statespace/_filters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters/_univariate_diffuse.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/_filters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/_filters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters/_inversions.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/_filters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters/_conventional.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/_filters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_filters/_univariate.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/_filters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/cfa_simulation_smoother.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/mlemodel.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/simulation_smoother.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/dynamic_factor.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_kalman_smoother.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/exponential_smoothing.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/dynamic_factor_mq.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_quarterly_ar1.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_representation.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_kalman_filter.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/statespace/_smoothers copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/_smoothers copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_classical.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/_smoothers copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_alternative.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/_smoothers copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/_smoothers copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_conventional.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/_smoothers copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_smoothers/_univariate.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/_smoothers copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/news.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/varmax.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/_initialization.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_decompose.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_kalman.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_fixed_params.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_save.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_news.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/kfas_helpers.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_impulse_responses.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_prediction.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_pickle.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_simulation_smoothing.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_cfa_tvpvar.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_representation.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_concentrated.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/manufac.dta -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_exact_initial_var1_mixed_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_smoothing_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_wpi1_ar3_matlab_ssm.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/cfa_tvpvar_posterior_mean.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_simulation_smoothing3.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_exact_initial_local_linear_trend_missing_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_sarimax.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_simulation_smoothing1.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_realgdpar_stata.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_simulation_smoothing0.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_wpi1_ar3_stata.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_varmax_stata.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_var_R_output.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/cfa_tvpvar_state_variates.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_intercepts_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_wpi1_missing_ar3_matlab_ssm.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/sm-0.9-sarimax.pkl -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_exact_initial_common_level_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_varmax.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_exact_initial_local_level_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_exact_initial_var1_measurement_error_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/cfa_tvpvar_Omega_22.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_simulation_smoothing4.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/cfa_tvpvar_v10.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_simulation_smoothing5.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/cfa_tvpvar_beta.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/cfa_tvpvar_invP.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/cfa_tvpvar_Si0.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_sarimax_coverage.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_var_misc.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_exact_initial_dfm_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_structural.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_smoothing3_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/exponential_smoothing_predict.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/statespace/tests/results/frbny_nowcast copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_news_222.mat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_news_112.mat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_221.mat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_222.mat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_111.mat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_22F.mat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_blocks_222.mat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_112.mat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_blocks_221.mat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_blocks_112.mat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/functions copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/functions/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/functions creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data/US copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data/US/2016-06-29.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data/US copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data/US/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data/US copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data/US/2016-07-29.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data/US copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/data copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast/Nowcasting copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_news_blocks_222.mat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_blocks_111.mat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_dfm_11F.mat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/frbny_nowcast/test_news_blocks_112.mat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results/frbny_nowcast copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_exact_initial_common_level_restricted_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/exponential_smoothing_params.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_simulation_smoothing2.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/exponential_smoothing_states.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/cfa_tvpvar_vi0.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_var_stata.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_smoothing_generalobscov_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/clark1989.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_dynamic_factor.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_exact_initial_var1_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_simulation_smoothing3_variates.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_clark1989_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/cfa_tvpvar_Omega_11.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_exact_initial_var1_missing_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_simulation_smoothing6.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_kalman_filter.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_smoothing2_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/cfa_tvpvar_S10.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_exact_initial_local_linear_trend_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_var_R.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/results/results_dynamic_factor_stata.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_options.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_chandrasekhar.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_initialization.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_structural.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_models.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_weights.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_conserve_memory.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_collapsed.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_cfa_simulation_smoothing.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_sarimax.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_forecasting.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_univariate.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_smoothing.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_var.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_multivariate_switch_univariate.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_varmax.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_dynamic_factor.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_mlemodel.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_tools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_simulate.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/statespace/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/adfvalues.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/ardl copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl/pss_critical_values.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/ardl copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/ardl copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl/model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/ardl creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/ardl/_pss_critical_values copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl/_pss_critical_values/pss.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/ardl/_pss_critical_values copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl/_pss_critical_values/pss-process.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/ardl/_pss_critical_values copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl/_pss_critical_values/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/ardl/_pss_critical_values creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/ardl/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl/tests/test_ardl.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/ardl/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ardl/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/ardl/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/holtwinters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/_smoothers.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/holtwinters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/holtwinters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/holtwinters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/holtwinters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/_exponential_smoothers.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/holtwinters creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/holtwinters/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/holtwinters/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/holtwinters/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/tests/results/housing-data.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/holtwinters/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/holtwinters/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/holtwinters/tests/test_holtwinters.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/holtwinters/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/innovations copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/innovations/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/innovations copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/innovations/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/innovations copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/innovations/_arma_innovations.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/innovations copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/innovations/arma_innovations.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/innovations creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/innovations/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/innovations/tests/test_arma_innovations.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/innovations/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/innovations/tests/test_cython_arma_innovations_fast.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/innovations/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/innovations/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/innovations/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/stl copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/mstl.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/stl copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/stl copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/_stl.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/stl creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/stl/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests/test_stl.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/stl/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/stl/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests/results/stl_co2.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/stl/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests/results/mstl_elec_vic.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/stl/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/stl/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests/results/mstl_test_results.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/stl/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests/results/stl_test_results.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/stl/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/stl/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stl/tests/test_mstl.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/stl/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/base copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base/tsa_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/base copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base/datetools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/base copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/base copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base/prediction.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/base creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/base/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base/tests/test_base.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/base/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base/tests/test_prediction.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/base/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/base/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base/tests/test_datetools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/base/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/base/tests/test_tsa_indexes.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/base/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arma_mle.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/forecasting copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/forecasting/stl.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/forecasting copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/forecasting/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/forecasting copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/forecasting/theta.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/forecasting creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/forecasting/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/forecasting/tests/test_stl.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/forecasting/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/forecasting/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/forecasting/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/forecasting/tests/test_theta.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/forecasting/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/ar_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/x13.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/regime_switching copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/markov_autoregression.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/regime_switching copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/regime_switching copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/markov_regression.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/regime_switching copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/_kim_smoother.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/regime_switching copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/markov_switching.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/regime_switching copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/_hamilton_filter.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/regime_switching creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/regime_switching/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests/test_markov_regression.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/regime_switching/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests/test_markov_switching.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/regime_switching/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests/test_markov_autoregression.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/regime_switching/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/regime_switching/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests/results/results_predict_rgnp.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/regime_switching/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/regime_switching/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests/results/results_predict_fedfunds.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/regime_switching/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests/results/mar_filardo.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/regime_switching/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/regime_switching/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/regime_switching/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/varma_process.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/descriptivestats.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/vector_ar copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/svar_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/irf.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/var_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/hypothesis_test_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/util.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/plotting.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/output.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/vecm.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/vector_ar/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_lagorder.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_granger_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realcons_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_Sigmau.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_granger_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_fc5.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_fc5.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_ir.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_diag.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_ir.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_granger_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_lagorder.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_inst_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/parse_jmulti_vecm_output.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_diag.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realcons.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_diag.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realcons_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realcons_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_inst_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_lagorder.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realgdp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_diag.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_inst_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realgdp_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_ir.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_ir.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_Sigmau.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realgdp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_lagorder.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_Sigmau.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_inst_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_fc5.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_lagorder.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_inst_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_diag.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_ir.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_fc5.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_inst_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realcons_realgdp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_ir.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_lagorder.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realgdp_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_fc5.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_fc5.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_ir.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_Sigmau.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_inst_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_lagorder.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_Sigmau.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/parse_jmulti_var_output.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_Sigmau.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_diag.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_fc5.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_Sigmau.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_granger_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_diag.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_diag.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_granger_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_lagorder.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_fc5.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_lagorder.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_granger_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_lagorder.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_ir.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_diag.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_Sigmau.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realgdp_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_granger_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_granger_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_Sigmau.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_lagorder.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realcons.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_Sigmau.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_ir.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realcons.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_lagorder.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realcons_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_diag.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realgdp_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_Sigmau.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_fc5.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_inst_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_Sigmau.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realgdp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realgdp_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_ir.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_lagorder.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_ir.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_fc5.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_granger_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_inst_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_granger_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_ir.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_diag.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realgdp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_granger_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_fc5.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_granger_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_ir.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_fc5.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realcons_realgdp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_inst_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_granger_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_granger_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_lagorder.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_inst_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realcons.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realcons_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_granger_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realcons_realgdp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_diag.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_diag.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realgdp_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_Sigmau.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_lagorder.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_Sigmau.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_inst_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_diag.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_inst_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_granger_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_inst_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realcons_realgdp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_fc5.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_granger_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_ir.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_inst_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_Sigmau.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_fc5.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_diag.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_granger_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realcons_realinv.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_lagorder.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realcons.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_granger_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_granger_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_inst_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realcons_realgdp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_inst_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_ir.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_Sigmau.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_fc5.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_diag.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_inst_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realgdp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_ir.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_inst_causality_dp_r.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realcons_realgdp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_fc5.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realgdp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realcons.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_inst_causality_r_dp.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/JMulTi_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/example_svar.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/test_var_jmulti.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/vector_ar/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results/e6.dat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results/results_svar_st.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results/results_var_data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results/results_var.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results/e5.dat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results/vars_results.npz -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results/e3.dat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results/e2.dat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results/e1.dat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results/e4.dat -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/results/results_svar.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/test_coint.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/test_svar.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/test_vecm.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/vector_ar/tests/Matlab_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/Matlab_results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/Matlab_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/Matlab_results/test_coint.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests/Matlab_results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/vector_ar/tests/test_var.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/vector_ar/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/mlemodel.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/stattools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/deterministic.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tsatools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/arima_process.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/seasonal.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/interp copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/interp/denton.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/interp copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/interp/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/interp creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/interp/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/interp/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/interp/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/interp/tests/test_denton.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/interp/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/_bds.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/coint_tables.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/filters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters/cf_filter.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/filters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters/bk_filter.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/filters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters/hp_filter.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/filters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters/filtertools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/filters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/filters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/filters copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters/_utils.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/filters creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/filters/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters/tests/test_filters.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/filters/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/filters/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/filters/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters/tests/results/filter_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/filters/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/filters/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/filters/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/exponential_smoothing copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/exponential_smoothing/initialization.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/exponential_smoothing copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/exponential_smoothing/_ets_smooth.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/exponential_smoothing copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/exponential_smoothing/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/exponential_smoothing copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/exponential_smoothing/base.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/exponential_smoothing copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/exponential_smoothing/ets.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/exponential_smoothing creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/test_arima_process.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/test_ar.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/test_stattools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/test_adfuller_lag.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/yhat_exact_c.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/yhat_css_nc.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/y_arma_data.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/rgnpq.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/rgnp.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/ARMLEConstantPredict.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/results_ar_forecast_mle_dynamic.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/AROLSNoConstantPredict.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/arima111_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/yhat_css_c.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/results_arima_exog_forecasts_css.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/gnpdef.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/fit_ets_results_seasonal.json -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/resids_exact_nc.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/results_arima_forecasts_all_mle_diff.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/arima111_forecasts.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/resids_exact_c.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/AROLSConstantPredict.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/arima111nc_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/resids_css_nc.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/bds_data.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/arima112nc_css_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/results_arma.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/results_process.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/yhat_exact_nc.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/bds_results.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/arima112nc_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/results_arima_exog_forecasts_mle.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/savedrvs.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/results_arma_forecasts.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/results_arima_forecasts_all_css_diff.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/resids_css_c.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/fit_ets_results_nonseasonal.json -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/lutkepohl2.dta -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/results_arma_acf.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/arima211nc_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/results_arima_forecasts_all_css.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/results_arima.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/arima211nc_css_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/arima111_css_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/arima212_forecast.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/arima112_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/stkprc.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/arima211_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/arima211_css_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/rand10000.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/arima111nc_css_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/arima112_css_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/results_arima_forecasts.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/results_arima_forecasts_all_mle.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/make_arma.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/results_ccf.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/results_ar.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/results_corrgram.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/datamlw_tls.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/results/fit_ets_results.json -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/test_exponential_smoothing.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/test_seasonal.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/test_x13.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/test_deterministic.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/test_tsa_tools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tsa/tests/test_bds.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tsa/tests creating build/bdist.linux-x86_64/wheel/statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/optimizer.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/_screening.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/_parameter_inference.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/elastic_net.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/transform.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/wrapper.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/_prediction_inference.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/l1_cvxopt.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/_penalties.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/_constraints.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/covtype.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/_penalized.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/l1_solvers_common.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/distributed_estimation.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base copying build/lib.linux-x86_64-cpython-313/statsmodels/base/l1_slsqp.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base creating build/bdist.linux-x86_64/wheel/statsmodels/base/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/base/tests/test_data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/base/tests/test_penalized.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/base/tests/test_optimize.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/base/tests/test_predict.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/base/tests/test_screening.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/base/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/base/tests/test_generic_methods.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/base/tests/test_transform.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/base/tests/test_shrink_pickle.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/base/tests/test_distributed_estimation.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/base/tests/test_penalties.py -> build/bdist.linux-x86_64/wheel/./statsmodels/base/tests creating build/bdist.linux-x86_64/wheel/statsmodels/compat copying build/lib.linux-x86_64-cpython-313/statsmodels/compat/patsy.py -> build/bdist.linux-x86_64/wheel/./statsmodels/compat copying build/lib.linux-x86_64-cpython-313/statsmodels/compat/pandas.py -> build/bdist.linux-x86_64/wheel/./statsmodels/compat copying build/lib.linux-x86_64-cpython-313/statsmodels/compat/scipy.py -> build/bdist.linux-x86_64/wheel/./statsmodels/compat copying build/lib.linux-x86_64-cpython-313/statsmodels/compat/python.py -> build/bdist.linux-x86_64/wheel/./statsmodels/compat copying build/lib.linux-x86_64-cpython-313/statsmodels/compat/_scipy_multivariate_t.py -> build/bdist.linux-x86_64/wheel/./statsmodels/compat copying build/lib.linux-x86_64-cpython-313/statsmodels/compat/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/compat copying build/lib.linux-x86_64-cpython-313/statsmodels/compat/numpy.py -> build/bdist.linux-x86_64/wheel/./statsmodels/compat copying build/lib.linux-x86_64-cpython-313/statsmodels/compat/platform.py -> build/bdist.linux-x86_64/wheel/./statsmodels/compat copying build/lib.linux-x86_64-cpython-313/statsmodels/compat/pytest.py -> build/bdist.linux-x86_64/wheel/./statsmodels/compat creating build/bdist.linux-x86_64/wheel/statsmodels/compat/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/compat/tests/test_itercompat.py -> build/bdist.linux-x86_64/wheel/./statsmodels/compat/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/compat/tests/test_scipy_compat.py -> build/bdist.linux-x86_64/wheel/./statsmodels/compat/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/compat/tests/test_pandas.py -> build/bdist.linux-x86_64/wheel/./statsmodels/compat/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/compat/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/compat/tests creating build/bdist.linux-x86_64/wheel/statsmodels/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/_prediction.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/quantile_regression.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/dimred.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/mixed_linear_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/recursive_ls.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/feasible_gls.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/rolling.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/linear_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/_tools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/process_regression.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression creating build/bdist.linux-x86_64/wheel/statsmodels/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/test_dimred.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/test_recursive_ls.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/test_theil.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/test_glsar_gretl.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/test_predict.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/test_rolling.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests creating build/bdist.linux-x86_64/wheel/statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/lme06.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/leverage_influence_ols_nostars.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/lme04.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/generate_lme.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/results_rls_R.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/lme09.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/lme07.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/lme10.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/lme05.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/lme01.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/results_quantile_regression.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/macro_gr_corc_stata.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/lme02.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/results_theil_textile.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/results_rls_stata.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/lme00.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/dietox.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/lme08.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/lme_r_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/results_macro_ols_robust.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/lme03.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/generate_lasso.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/glmnet_r_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/lme11.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/lasso_data.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/results_grunfeld_ols_robust_cluster.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/results_regression.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/pastes.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/results/theil_textile_predict.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/test_glsar_stata.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/test_processreg.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/test_lme.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/test_regression.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/test_robustcov.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/test_quantile_regression.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/test_cov.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/regression/tests/test_tools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/regression/tests creating build/bdist.linux-x86_64/wheel/statsmodels/discrete copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/discrete_margins.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/discrete_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/truncated_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/diagnostic.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/conditional_models.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/_diagnostics_count.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/count_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete creating build/bdist.linux-x86_64/wheel/statsmodels/discrete/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/test_truncated_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/test_constrained.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/test_diagnostic.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/test_predict.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests creating build/bdist.linux-x86_64/wheel/statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/ships.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/results_truncated.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/poisson_resid.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/results_glm_logit_constrained.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/results_predict.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/results_count_margins.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/predict_prob_poisson.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/phat_mnlogit.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/results_truncated_st.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/mn_logit_summary.txt -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/results_count_robust_cluster.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/nbinom_resids.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/sm3533.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/yhat_mnlogit.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/results_poisson_constrained.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/mnlogit_resid.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/yhat_poisson.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/results/results_discrete.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/test_conditional.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/test_discrete.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/test_margins.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/test_sandwich_cov.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/discrete/tests/test_count_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/discrete/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/decorators.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/numdiff.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/rootfinding.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/grouputils.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/sm_exceptions.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/eval_measures.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/web.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/testing.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/typing.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/_test_runner.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/catadd.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/tools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/parallel.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/transform_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/docstring.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/print_version.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools creating build/bdist.linux-x86_64/wheel/statsmodels/tools/validation copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/validation/decorators.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/validation copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/validation/validation.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/validation copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/validation/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/validation creating build/bdist.linux-x86_64/wheel/statsmodels/tools/validation/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/validation/tests/test_validation.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/validation/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/validation/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/validation/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/rng_qrng.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/_testing.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/linalg.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/sequences.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools creating build/bdist.linux-x86_64/wheel/statsmodels/tools/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests/test_linalg.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests/test_catadd.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests/test_data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests/test_eval_measures.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests/test_testing.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests/test_sequences.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests/test_decorators.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests/test_web.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests/test_transform_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests/test_grouputils.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests/test_parallel.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests/test_numdiff.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests/test_tools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests/test_docstring.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tools/tests/test_rootfinding.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tools/tests creating build/bdist.linux-x86_64/wheel/statsmodels/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/empirical_distribution.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions creating build/bdist.linux-x86_64/wheel/statsmodels/distributions/copula copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula/copulas.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions/copula copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula/_special.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions/copula copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula/extreme_value.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions/copula copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula/transforms.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions/copula copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions/copula copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions/copula copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula/archimedean.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions/copula copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula/depfunc_ev.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions/copula copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula/elliptical.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions/copula copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/copula/other_copulas.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions/copula copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/tools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/bernstein.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/discrete.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/edgeworth.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions creating build/bdist.linux-x86_64/wheel/statsmodels/distributions/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/tests/test_ecdf.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/tests/test_discrete.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/tests/test_bernstein.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/tests/test_edgeworth.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/tests/test_mixture.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/tests/test_tools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/distributions/mixture_rvs.py -> build/bdist.linux-x86_64/wheel/./statsmodels/distributions creating build/bdist.linux-x86_64/wheel/statsmodels/miscmodels copying build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/count.py -> build/bdist.linux-x86_64/wheel/./statsmodels/miscmodels copying build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/try_mlecov.py -> build/bdist.linux-x86_64/wheel/./statsmodels/miscmodels copying build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/ordinal_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/miscmodels copying build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/miscmodels copying build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/miscmodels copying build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tmodel.py -> build/bdist.linux-x86_64/wheel/./statsmodels/miscmodels copying build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/nonlinls.py -> build/bdist.linux-x86_64/wheel/./statsmodels/miscmodels creating build/bdist.linux-x86_64/wheel/statsmodels/miscmodels/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests/results_tmodel.py -> build/bdist.linux-x86_64/wheel/./statsmodels/miscmodels/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests/test_generic_mle.py -> build/bdist.linux-x86_64/wheel/./statsmodels/miscmodels/tests creating build/bdist.linux-x86_64/wheel/statsmodels/miscmodels/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/miscmodels/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests/results/results_ordinal_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/miscmodels/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests/results/ologit_ucla.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/miscmodels/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/miscmodels/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests/test_poisson.py -> build/bdist.linux-x86_64/wheel/./statsmodels/miscmodels/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests/test_tmodel.py -> build/bdist.linux-x86_64/wheel/./statsmodels/miscmodels/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/miscmodels/tests/test_ordinal_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/miscmodels/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/setup.cfg -> build/bdist.linux-x86_64/wheel/./statsmodels creating build/bdist.linux-x86_64/wheel/statsmodels/gam copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/generalized_additive_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/gam copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/gam copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/gam creating build/bdist.linux-x86_64/wheel/statsmodels/gam/gam_cross_validation copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/gam_cross_validation/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/gam_cross_validation copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/gam_cross_validation/cross_validators.py -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/gam_cross_validation copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/gam_cross_validation/gam_cross_validation.py -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/gam_cross_validation copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/smooth_basis.py -> build/bdist.linux-x86_64/wheel/./statsmodels/gam copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/gam_penalties.py -> build/bdist.linux-x86_64/wheel/./statsmodels/gam creating build/bdist.linux-x86_64/wheel/statsmodels/gam/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/test_smooth_basis.py -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/test_penalized.py -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/tests creating build/bdist.linux-x86_64/wheel/statsmodels/gam/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results/cubic_cyclic_splines_from_mgcv.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results/gam_PIRLS_results.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results/prediction_from_mgcv.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results/results_mpg_bs.py -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results/autos_exog.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results/motorcycle.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results/results_pls.py -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results/autos_predict.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results/logit_gam_mgcv.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results/autos.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/results/results_mpg_bs_poisson.py -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/gam/tests/test_gam.py -> build/bdist.linux-x86_64/wheel/./statsmodels/gam/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/LICENSE.txt -> build/bdist.linux-x86_64/wheel/./statsmodels copying build/lib.linux-x86_64-cpython-313/statsmodels/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels creating build/bdist.linux-x86_64/wheel/statsmodels/othermod copying build/lib.linux-x86_64-cpython-313/statsmodels/othermod/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/othermod copying build/lib.linux-x86_64-cpython-313/statsmodels/othermod/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/othermod copying build/lib.linux-x86_64-cpython-313/statsmodels/othermod/betareg.py -> build/bdist.linux-x86_64/wheel/./statsmodels/othermod creating build/bdist.linux-x86_64/wheel/statsmodels/othermod/tests creating build/bdist.linux-x86_64/wheel/statsmodels/othermod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/othermod/tests/results/foodexpenditure.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/othermod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/othermod/tests/results/resid_methylation.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/othermod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/othermod/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/othermod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/othermod/tests/results/results_betareg.py -> build/bdist.linux-x86_64/wheel/./statsmodels/othermod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/othermod/tests/results/methylation-test.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/othermod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/othermod/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/othermod/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/othermod/tests/test_beta.py -> build/bdist.linux-x86_64/wheel/./statsmodels/othermod/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels creating build/bdist.linux-x86_64/wheel/statsmodels/duration copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/_kernel_estimates.py -> build/bdist.linux-x86_64/wheel/./statsmodels/duration copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/hazard_regression.py -> build/bdist.linux-x86_64/wheel/./statsmodels/duration copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/duration copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/duration copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/survfunc.py -> build/bdist.linux-x86_64/wheel/./statsmodels/duration creating build/bdist.linux-x86_64/wheel/statsmodels/duration/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/test_phreg.py -> build/bdist.linux-x86_64/wheel/./statsmodels/duration/tests creating build/bdist.linux-x86_64/wheel/statsmodels/duration/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results/survival_r_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/duration/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results/bmt.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/duration/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results/survival_data_50_2.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/duration/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results/bmt_results.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/duration/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results/survival_data_1000_10.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/duration/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results/phreg_gentests.py -> build/bdist.linux-x86_64/wheel/./statsmodels/duration/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results/survival_data_100_5.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/duration/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/duration/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results/survival_data_50_1.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/duration/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results/survival_enet_r_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/duration/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/results/survival_data_20_1.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/duration/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/duration/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/duration/tests/test_survfunc.py -> build/bdist.linux-x86_64/wheel/./statsmodels/duration/tests creating build/bdist.linux-x86_64/wheel/statsmodels/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/kernel_density.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/kernel_regression.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/kernels_asymmetric.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/kdetools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/_smoothers_lowess.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/smoothers_lowess_old.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/linbin.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/_kernel_base.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/smoothers_lowess.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/kernels.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric creating build/bdist.linux-x86_64/wheel/statsmodels/nonparametric/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/test_bandwidths.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/test_kernels.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/test_asymmetric.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests creating build/bdist.linux-x86_64/wheel/statsmodels/nonparametric/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results/results_kcde.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results/test_lowess_delta.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results/test_lowess_frac.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results/results_kde_fft.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results/results_kde_univ_weights.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results/test_lowess_simple.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results/test_lowess_iter.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results/results_kde_weights.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results/results_kernel_regression.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/results/results_kde.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/test_kde.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/test_kernel_regression.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/test_lowess.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/tests/test_kernel_density.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/kde.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/nonparametric/bandwidths.py -> build/bdist.linux-x86_64/wheel/./statsmodels/nonparametric creating build/bdist.linux-x86_64/wheel/statsmodels/emplike copying build/lib.linux-x86_64-cpython-313/statsmodels/emplike/aft_el.py -> build/bdist.linux-x86_64/wheel/./statsmodels/emplike copying build/lib.linux-x86_64-cpython-313/statsmodels/emplike/descriptive.py -> build/bdist.linux-x86_64/wheel/./statsmodels/emplike copying build/lib.linux-x86_64-cpython-313/statsmodels/emplike/originregress.py -> build/bdist.linux-x86_64/wheel/./statsmodels/emplike copying build/lib.linux-x86_64-cpython-313/statsmodels/emplike/elregress.py -> build/bdist.linux-x86_64/wheel/./statsmodels/emplike copying build/lib.linux-x86_64-cpython-313/statsmodels/emplike/elanova.py -> build/bdist.linux-x86_64/wheel/./statsmodels/emplike copying build/lib.linux-x86_64-cpython-313/statsmodels/emplike/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/emplike copying build/lib.linux-x86_64-cpython-313/statsmodels/emplike/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/emplike creating build/bdist.linux-x86_64/wheel/statsmodels/emplike/tests creating build/bdist.linux-x86_64/wheel/statsmodels/emplike/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/emplike/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests/results/el_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/emplike/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests/test_descriptive.py -> build/bdist.linux-x86_64/wheel/./statsmodels/emplike/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/emplike/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests/test_anova.py -> build/bdist.linux-x86_64/wheel/./statsmodels/emplike/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests/test_regression.py -> build/bdist.linux-x86_64/wheel/./statsmodels/emplike/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests/test_aft.py -> build/bdist.linux-x86_64/wheel/./statsmodels/emplike/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/emplike/tests/test_origin.py -> build/bdist.linux-x86_64/wheel/./statsmodels/emplike/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/_version.py -> build/bdist.linux-x86_64/wheel/./statsmodels creating build/bdist.linux-x86_64/wheel/statsmodels/datasets creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/china_smoking copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/china_smoking/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/china_smoking copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/china_smoking/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/china_smoking copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/china_smoking/china_smoking.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/china_smoking creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/sunspots copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/sunspots/sunspots.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/sunspots copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/sunspots/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/sunspots copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/sunspots/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/sunspots copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/template_data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/star98 copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/star98/star98.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/star98 copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/star98/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/star98 copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/star98/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/star98 creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/committee copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/committee/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/committee copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/committee/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/committee copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/committee/committee.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/committee creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/elnino copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/elnino/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/elnino copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/elnino/elnino.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/elnino copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/elnino/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/elnino creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/copper copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/copper/copper.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/copper copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/copper/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/copper copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/copper/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/copper creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/strikes copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/strikes/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/strikes copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/strikes/strikes.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/strikes copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/strikes/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/strikes creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/heart copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/heart/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/heart copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/heart/heart.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/heart copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/heart/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/heart creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/modechoice copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/modechoice/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/modechoice copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/modechoice/modechoice.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/modechoice copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/modechoice/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/modechoice creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/spector copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/spector/spector.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/spector copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/spector/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/spector copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/spector/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/spector creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/randhie copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/randhie/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/randhie copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/randhie/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/randhie copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/randhie/randhie.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/randhie creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/interest_inflation copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/interest_inflation/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/interest_inflation copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/interest_inflation/E6.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/interest_inflation copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/interest_inflation/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/interest_inflation copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/interest_inflation/E6_jmulti.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/interest_inflation copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/anes96 copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/anes96/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/anes96 copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/anes96/anes96.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/anes96 copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/anes96/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/anes96 creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/danish_data copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/danish_data/data.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/danish_data copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/danish_data/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/danish_data copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/danish_data/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/danish_data creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/nile copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/nile/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/nile copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/nile/nile.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/nile copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/nile/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/nile creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/co2 copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/co2/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/co2 copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/co2/co2.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/co2 copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/co2/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/co2 creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/longley copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/longley/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/longley copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/longley/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/longley copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/longley/longley.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/longley creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/fair copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/fair/fair.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/fair copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/fair/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/fair copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/fair/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/fair copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/fair/fair_pt.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/fair creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/statecrime copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/statecrime/statecrime.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/statecrime copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/statecrime/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/statecrime copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/statecrime/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/statecrime creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/stackloss copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/stackloss/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/stackloss copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/stackloss/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/stackloss copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/stackloss/stackloss.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/stackloss creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/engel copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/engel/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/engel copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/engel/engel.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/engel copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/engel/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/engel copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/utils.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/grunfeld copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/grunfeld/grunfeld.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/grunfeld copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/grunfeld/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/grunfeld copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/grunfeld/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/grunfeld creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/cpunish copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/cpunish/cpunish.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/cpunish copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/cpunish/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/cpunish copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/cpunish/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/cpunish creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/fertility copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/fertility/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/fertility copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/fertility/fertility.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/fertility copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/fertility/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/fertility creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/cancer copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/cancer/cancer.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/cancer copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/cancer/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/cancer copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/cancer/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/cancer creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/elec_equip copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/elec_equip/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/elec_equip copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/elec_equip/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/elec_equip copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/elec_equip/elec_equip.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/elec_equip creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/ccard copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/ccard/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/ccard copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/ccard/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/ccard copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/ccard/ccard.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/ccard creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/macrodata copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/macrodata/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/macrodata copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/macrodata/macrodata.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/macrodata copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/macrodata/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/macrodata copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/macrodata/macrodata.dta -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/macrodata creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/tests/test_data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/tests/test_utils.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/tests creating build/bdist.linux-x86_64/wheel/statsmodels/datasets/scotland copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/scotland/data.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/scotland copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/scotland/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/scotland copying build/lib.linux-x86_64-cpython-313/statsmodels/datasets/scotland/scotvote.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/datasets/scotland creating build/bdist.linux-x86_64/wheel/statsmodels/imputation copying build/lib.linux-x86_64-cpython-313/statsmodels/imputation/mice.py -> build/bdist.linux-x86_64/wheel/./statsmodels/imputation copying build/lib.linux-x86_64-cpython-313/statsmodels/imputation/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/imputation copying build/lib.linux-x86_64-cpython-313/statsmodels/imputation/ros.py -> build/bdist.linux-x86_64/wheel/./statsmodels/imputation copying build/lib.linux-x86_64-cpython-313/statsmodels/imputation/bayes_mi.py -> build/bdist.linux-x86_64/wheel/./statsmodels/imputation creating build/bdist.linux-x86_64/wheel/statsmodels/imputation/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/imputation/tests/test_ros.py -> build/bdist.linux-x86_64/wheel/./statsmodels/imputation/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/imputation/tests/test_bayes_mi.py -> build/bdist.linux-x86_64/wheel/./statsmodels/imputation/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/imputation/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/imputation/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/imputation/tests/test_mice.py -> build/bdist.linux-x86_64/wheel/./statsmodels/imputation/tests creating build/bdist.linux-x86_64/wheel/statsmodels/graphics copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tsaplots.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/_regressionplots_doc.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/functional.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/agreement.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/regressionplots.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/factorplots.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/plot_grids.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/correlation.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/gofplots.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/boxplots.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/plottools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tukeyplot.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/mosaicplot.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/dotplots.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/utils.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics creating build/bdist.linux-x86_64/wheel/statsmodels/graphics/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests/test_correlation.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests/test_agreement.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests/test_tsaplots.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests/test_gofplots.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests/test_factorplots.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests/test_regressionplots.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests/test_boxplots.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests/test_functional.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests/test_mosaicplot.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/graphics/tests/test_dotplot.py -> build/bdist.linux-x86_64/wheel/./statsmodels/graphics/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/conftest.py -> build/bdist.linux-x86_64/wheel/./statsmodels creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/pca.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/descstats.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox/mcevaluate copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/mcevaluate/arma.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/mcevaluate copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/mcevaluate/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/mcevaluate creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats/runs.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats/multicomp.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats/stats_mstats_short.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats/diagnostic.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats/stats_dhuard.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats/contrast_tools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/stats creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats/tests/test_runs.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats/tests/test_multicomp.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/stats/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/stats/ex_newtests.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/stats copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/bspline.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/multilinear.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/infotheo.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/rls.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/gam.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa/try_arma_more.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa/try_fi.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa/example_arma.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa/diffusion.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa/diffusion2.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa/try_var_convolve.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa/fftarma.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa/varma.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tsa copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tsa/movstat.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tsa creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/predstd.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/onewaygls.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/treewalkerclass.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/gmm.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/kernridgeregress_class.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/try_ols_anova.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/example_kernridge.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/runmnl.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/penalized.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/ols_anova_original.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/ar_panel.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/sympy_diff.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/try_treewalker.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests/test_gmm_poisson.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests/results_gmm_griliches_iter.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests/test_gmm.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests/griliches76.dta -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests/results_gmm_poisson.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests/results_ivreg2_griliches.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests/racd10data_with_transformed.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/tests/results_gmm_griliches.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/anova_nistcertified.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/regression/try_catdata.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/regression creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tools/cross_val.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tools/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tools/mctools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tools/tools_pca.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tools copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tools/try_mctools.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tools creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/try_max.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/otherdist.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/multivariate.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/mv_normal.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/try_pot.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/transformed.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/genpareto.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/estimators.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/quantize.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/sppatch.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/gof_new.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/transform_functions.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/extras.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/mv_measures.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox/distributions/examples copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/examples/ex_mvelliptical.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions/examples copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/examples/ex_gof.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions/examples copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/examples/ex_fitfr.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions/examples copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/examples/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions/examples copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/examples/ex_extras.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions/examples copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/examples/matchdist.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions/examples copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/examples/ex_transf2.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions/examples creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox/distributions/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests/test_norm_expan.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests/test_multivariate.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests/check_moments.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests/test_extras.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests/test_gof_new.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests/_est_fit.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests/test_transf.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/distributions/tests/distparams.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/distributions/tests creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox/archive copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/archive/linalg_decomp_1.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/archive copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/archive/tsa.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/archive copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/archive/linalg_covmat.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/archive copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/archive/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/archive copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox/datarich copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/datarich/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/datarich copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/datarich/factormodels.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/datarich creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/smoothers.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/dgp_examples.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/testdata.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/densityorthopoly.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/kernel_extras.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/kdecovclass.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/kernels.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/nonparametric copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/kde2.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/nonparametric creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox/nonparametric/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/tests/ex_smoothers.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/nonparametric/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/tests/test_smoothers.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/nonparametric/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/nonparametric/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/tests/ex_gam_new.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/nonparametric/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/tests/ex_gam_am_new.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/nonparametric/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/nonparametric/tests/test_kernel_extras.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/nonparametric/tests creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox/panel copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/panel copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel/sandwich_covariance_generic.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/panel copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel/panel_short.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/panel copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel/mixed.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/panel copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel/panelmod.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/panel copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel/correlation_structures.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/panel creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox/panel/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel/tests/test_random_panel.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/panel/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/panel/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/panel/random_panel.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/panel copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/sysreg.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/mle.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox creating build/bdist.linux-x86_64/wheel/statsmodels/sandbox/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tests/maketests_mlabwrap.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tests/savervs.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tests/test_predict_functional.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tests/test_pca.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/tests/test_gam.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/sandbox/predict_functional.py -> build/bdist.linux-x86_64/wheel/./statsmodels/sandbox creating build/bdist.linux-x86_64/wheel/statsmodels/robust copying build/lib.linux-x86_64-cpython-313/statsmodels/robust/norms.py -> build/bdist.linux-x86_64/wheel/./statsmodels/robust copying build/lib.linux-x86_64-cpython-313/statsmodels/robust/_qn.cpython-313-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/wheel/./statsmodels/robust copying build/lib.linux-x86_64-cpython-313/statsmodels/robust/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/robust copying build/lib.linux-x86_64-cpython-313/statsmodels/robust/scale.py -> build/bdist.linux-x86_64/wheel/./statsmodels/robust copying build/lib.linux-x86_64-cpython-313/statsmodels/robust/robust_linear_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/robust creating build/bdist.linux-x86_64/wheel/statsmodels/robust/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests/test_scale.py -> build/bdist.linux-x86_64/wheel/./statsmodels/robust/tests creating build/bdist.linux-x86_64/wheel/statsmodels/robust/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests/results/results_rlm.py -> build/bdist.linux-x86_64/wheel/./statsmodels/robust/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests/results/results_norms.py -> build/bdist.linux-x86_64/wheel/./statsmodels/robust/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/robust/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests/test_mquantiles.py -> build/bdist.linux-x86_64/wheel/./statsmodels/robust/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/robust/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests/test_norms.py -> build/bdist.linux-x86_64/wheel/./statsmodels/robust/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/robust/tests/test_rlm.py -> build/bdist.linux-x86_64/wheel/./statsmodels/robust/tests creating build/bdist.linux-x86_64/wheel/statsmodels/genmod copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/cov_struct.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/generalized_linear_model.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/bayes_mixed_glm.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/qif.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/generalized_estimating_equations.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod creating build/bdist.linux-x86_64/wheel/statsmodels/genmod/families copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/families/family.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/families copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/families/varfuncs.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/families copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/families/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/families copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/families/links.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/families creating build/bdist.linux-x86_64/wheel/statsmodels/genmod/families/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/families/tests/test_link.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/families/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/families/tests/test_family.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/families/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/families/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/families/tests creating build/bdist.linux-x86_64/wheel/statsmodels/genmod/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/gee_poisson_simulation_check.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/test_score_test.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/test_qif.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/test_constrained.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/test_bayes_mixed_glm.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/test_glm.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/gee_simulation_check.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/test_gee.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests creating build/bdist.linux-x86_64/wheel/statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/enet_binomial.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/stata_lbw_glm.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/gee_nominal_1.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/gee_ordinal_1.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/res_R_var_weight.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/results_glm.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/gee_linear_1.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/epil.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/gee_nested_linear_1.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/gee_generate_tests.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/medparlogresids.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/stata_cancer_glm.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/glmnet_r_results.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/iris.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/gee_logistic_1.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/enet_poisson.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/results_glm_poisson_weights.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/glm_test_resids.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/igaussident_resids.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/gee_poisson_1.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/inv_gaussian.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/stata_medpar1_glm.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/results_tweedie_aweights_nonrobust.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/results/elastic_net_generate_tests.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/test_gee_glm.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/gee_gaussian_simulation_check.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/gee_categorical_simulation_check.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/tests/test_glm_weights.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/genmod/_tweedie_compound_poisson.py -> build/bdist.linux-x86_64/wheel/./statsmodels/genmod creating build/bdist.linux-x86_64/wheel/statsmodels/multivariate copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/pca.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate creating build/bdist.linux-x86_64/wheel/statsmodels/multivariate/factor_rotation copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/factor_rotation/_analytic_rotation.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate/factor_rotation copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/factor_rotation/_wrappers.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate/factor_rotation copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/factor_rotation/_gpa_rotation.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate/factor_rotation copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/factor_rotation/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate/factor_rotation creating build/bdist.linux-x86_64/wheel/statsmodels/multivariate/factor_rotation/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/factor_rotation/tests/test_rotation.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate/factor_rotation/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/factor_rotation/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate/factor_rotation/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/multivariate_ols.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/factor.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/cancorr.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/plots.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/manova.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate creating build/bdist.linux-x86_64/wheel/statsmodels/multivariate/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests/test_multivariate_ols.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests/test_manova.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests/test_pca.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests/test_cancorr.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests/test_factor.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate/tests creating build/bdist.linux-x86_64/wheel/statsmodels/multivariate/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests/results/datamlw.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests/results/factor_data.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests/results/factors_stata.csv -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/multivariate/tests/test_ml_factor.py -> build/bdist.linux-x86_64/wheel/./statsmodels/multivariate/tests creating build/bdist.linux-x86_64/wheel/statsmodels/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tests/test_x13.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/tests/test_package.py -> build/bdist.linux-x86_64/wheel/./statsmodels/tests creating build/bdist.linux-x86_64/wheel/statsmodels/iolib copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/summary.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/foreign.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/summary2.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/api.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/openfile.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/table.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tableformatting.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/smpickle.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/stata_summary_examples.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib creating build/bdist.linux-x86_64/wheel/statsmodels/iolib/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests/test_table.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests/test_table_econpy.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests/test_pickle.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests/test_summary2.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests/test_summary_old.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib/tests creating build/bdist.linux-x86_64/wheel/statsmodels/iolib/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests/results/time_series_examples.dta -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests/results/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests/results/data_missing.dta -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests/results/macrodata.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib/tests/results copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests/__init__.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib/tests copying build/lib.linux-x86_64-cpython-313/statsmodels/iolib/tests/test_summary.py -> build/bdist.linux-x86_64/wheel/./statsmodels/iolib/tests running install_egg_info running egg_info creating statsmodels.egg-info writing statsmodels.egg-info/PKG-INFO writing dependency_links to statsmodels.egg-info/dependency_links.txt writing requirements to statsmodels.egg-info/requires.txt writing top-level names to statsmodels.egg-info/top_level.txt writing manifest file 'statsmodels.egg-info/SOURCES.txt' dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/arrayscalars.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarrayobject.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ndarraytypes.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/npy_math.h won't be automatically included in the manifest: the path must be relative dependency /usr/lib/x86_64-linux-gnu/python3-numpy/numpy/_core/include/numpy/ufuncobject.h won't be automatically included in the manifest: the path must be relative reading manifest file 'statsmodels.egg-info/SOURCES.txt' reading manifest template 'MANIFEST.in' warning: no files found matching '*.pxi' anywhere in distribution warning: no previously-included files matching '*' found under directory 'dist' warning: no previously-included files found matching 'docs/source/generated/*' warning: no files found matching '*' under directory 'docs/sphinxext' warning: no files found matching '*' under directory 'docs/themes' warning: no previously-included files matching '*' found under directory 'docs/build' warning: no previously-included files matching '*' found under directory 'docs/build/htmlhelp' warning: no files found matching 'statsmodels/statsmodelsdoc.chm' no previously-included directories found matching '*/__pycache__' warning: no previously-included files matching '*~' found anywhere in distribution warning: no previously-included files matching '*.swp' found anywhere in distribution warning: no previously-included files matching '*.pyc' found anywhere in distribution warning: no previously-included files matching '*.pyo' found anywhere in distribution warning: no previously-included files matching '*.bak' found anywhere in distribution adding license file 'LICENSE.txt' writing manifest file 'statsmodels.egg-info/SOURCES.txt' Copying statsmodels.egg-info to build/bdist.linux-x86_64/wheel/./statsmodels-0.14.5+dfsg.egg-info running install_scripts creating build/bdist.linux-x86_64/wheel/statsmodels-0.14.5+dfsg.dist-info/WHEEL creating '/build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/.tmp-zurui74y/statsmodels-0.14.5+dfsg-cp313-cp313-linux_x86_64.whl' and adding 'build/bdist.linux-x86_64/wheel' to it adding 'statsmodels/LICENSE.txt' adding 'statsmodels/__init__.py' adding 'statsmodels/_version.py' adding 'statsmodels/api.py' adding 'statsmodels/conftest.py' adding 'statsmodels/setup.cfg' adding 'statsmodels/base/__init__.py' adding 'statsmodels/base/_constraints.py' adding 'statsmodels/base/_parameter_inference.py' adding 'statsmodels/base/_penalized.py' adding 'statsmodels/base/_penalties.py' adding 'statsmodels/base/_prediction_inference.py' adding 'statsmodels/base/_screening.py' adding 'statsmodels/base/covtype.py' adding 'statsmodels/base/data.py' adding 'statsmodels/base/distributed_estimation.py' adding 'statsmodels/base/elastic_net.py' adding 'statsmodels/base/l1_cvxopt.py' adding 'statsmodels/base/l1_slsqp.py' adding 'statsmodels/base/l1_solvers_common.py' adding 'statsmodels/base/model.py' adding 'statsmodels/base/optimizer.py' adding 'statsmodels/base/transform.py' adding 'statsmodels/base/wrapper.py' adding 'statsmodels/base/tests/__init__.py' adding 'statsmodels/base/tests/test_data.py' adding 'statsmodels/base/tests/test_distributed_estimation.py' adding 'statsmodels/base/tests/test_generic_methods.py' adding 'statsmodels/base/tests/test_optimize.py' adding 'statsmodels/base/tests/test_penalized.py' adding 'statsmodels/base/tests/test_penalties.py' adding 'statsmodels/base/tests/test_predict.py' adding 'statsmodels/base/tests/test_screening.py' adding 'statsmodels/base/tests/test_shrink_pickle.py' adding 'statsmodels/base/tests/test_transform.py' adding 'statsmodels/compat/__init__.py' adding 'statsmodels/compat/_scipy_multivariate_t.py' adding 'statsmodels/compat/numpy.py' adding 'statsmodels/compat/pandas.py' adding 'statsmodels/compat/patsy.py' adding 'statsmodels/compat/platform.py' adding 'statsmodels/compat/pytest.py' adding 'statsmodels/compat/python.py' adding 'statsmodels/compat/scipy.py' adding 'statsmodels/compat/tests/__init__.py' adding 'statsmodels/compat/tests/test_itercompat.py' adding 'statsmodels/compat/tests/test_pandas.py' adding 'statsmodels/compat/tests/test_scipy_compat.py' adding 'statsmodels/datasets/__init__.py' adding 'statsmodels/datasets/template_data.py' adding 'statsmodels/datasets/utils.py' adding 'statsmodels/datasets/anes96/__init__.py' adding 'statsmodels/datasets/anes96/anes96.csv' adding 'statsmodels/datasets/anes96/data.py' adding 'statsmodels/datasets/cancer/__init__.py' adding 'statsmodels/datasets/cancer/cancer.csv' adding 'statsmodels/datasets/cancer/data.py' adding 'statsmodels/datasets/ccard/__init__.py' adding 'statsmodels/datasets/ccard/ccard.csv' adding 'statsmodels/datasets/ccard/data.py' adding 'statsmodels/datasets/china_smoking/__init__.py' adding 'statsmodels/datasets/china_smoking/china_smoking.csv' adding 'statsmodels/datasets/china_smoking/data.py' adding 'statsmodels/datasets/co2/__init__.py' adding 'statsmodels/datasets/co2/co2.csv' adding 'statsmodels/datasets/co2/data.py' adding 'statsmodels/datasets/committee/__init__.py' adding 'statsmodels/datasets/committee/committee.csv' adding 'statsmodels/datasets/committee/data.py' adding 'statsmodels/datasets/copper/__init__.py' adding 'statsmodels/datasets/copper/copper.csv' adding 'statsmodels/datasets/copper/data.py' adding 'statsmodels/datasets/cpunish/__init__.py' adding 'statsmodels/datasets/cpunish/cpunish.csv' adding 'statsmodels/datasets/cpunish/data.py' adding 'statsmodels/datasets/danish_data/__init__.py' adding 'statsmodels/datasets/danish_data/data.csv' adding 'statsmodels/datasets/danish_data/data.py' adding 'statsmodels/datasets/elec_equip/__init__.py' adding 'statsmodels/datasets/elec_equip/data.py' adding 'statsmodels/datasets/elec_equip/elec_equip.csv' adding 'statsmodels/datasets/elnino/__init__.py' adding 'statsmodels/datasets/elnino/data.py' adding 'statsmodels/datasets/elnino/elnino.csv' adding 'statsmodels/datasets/engel/__init__.py' adding 'statsmodels/datasets/engel/data.py' adding 'statsmodels/datasets/engel/engel.csv' adding 'statsmodels/datasets/fair/__init__.py' adding 'statsmodels/datasets/fair/data.py' adding 'statsmodels/datasets/fair/fair.csv' adding 'statsmodels/datasets/fair/fair_pt.csv' adding 'statsmodels/datasets/fertility/__init__.py' adding 'statsmodels/datasets/fertility/data.py' adding 'statsmodels/datasets/fertility/fertility.csv' adding 'statsmodels/datasets/grunfeld/__init__.py' adding 'statsmodels/datasets/grunfeld/data.py' adding 'statsmodels/datasets/grunfeld/grunfeld.csv' adding 'statsmodels/datasets/heart/__init__.py' adding 'statsmodels/datasets/heart/data.py' adding 'statsmodels/datasets/heart/heart.csv' adding 'statsmodels/datasets/interest_inflation/E6.csv' adding 'statsmodels/datasets/interest_inflation/E6_jmulti.csv' adding 'statsmodels/datasets/interest_inflation/__init__.py' adding 'statsmodels/datasets/interest_inflation/data.py' adding 'statsmodels/datasets/longley/__init__.py' adding 'statsmodels/datasets/longley/data.py' adding 'statsmodels/datasets/longley/longley.csv' adding 'statsmodels/datasets/macrodata/__init__.py' adding 'statsmodels/datasets/macrodata/data.py' adding 'statsmodels/datasets/macrodata/macrodata.csv' adding 'statsmodels/datasets/macrodata/macrodata.dta' adding 'statsmodels/datasets/modechoice/__init__.py' adding 'statsmodels/datasets/modechoice/data.py' adding 'statsmodels/datasets/modechoice/modechoice.csv' adding 'statsmodels/datasets/nile/__init__.py' adding 'statsmodels/datasets/nile/data.py' adding 'statsmodels/datasets/nile/nile.csv' adding 'statsmodels/datasets/randhie/__init__.py' adding 'statsmodels/datasets/randhie/data.py' adding 'statsmodels/datasets/randhie/randhie.csv' adding 'statsmodels/datasets/scotland/__init__.py' adding 'statsmodels/datasets/scotland/data.py' adding 'statsmodels/datasets/scotland/scotvote.csv' adding 'statsmodels/datasets/spector/__init__.py' adding 'statsmodels/datasets/spector/data.py' adding 'statsmodels/datasets/spector/spector.csv' adding 'statsmodels/datasets/stackloss/__init__.py' adding 'statsmodels/datasets/stackloss/data.py' adding 'statsmodels/datasets/stackloss/stackloss.csv' adding 'statsmodels/datasets/star98/__init__.py' adding 'statsmodels/datasets/star98/data.py' adding 'statsmodels/datasets/star98/star98.csv' adding 'statsmodels/datasets/statecrime/__init__.py' adding 'statsmodels/datasets/statecrime/data.py' adding 'statsmodels/datasets/statecrime/statecrime.csv' adding 'statsmodels/datasets/strikes/__init__.py' adding 'statsmodels/datasets/strikes/data.py' adding 'statsmodels/datasets/strikes/strikes.csv' adding 'statsmodels/datasets/sunspots/__init__.py' adding 'statsmodels/datasets/sunspots/data.py' adding 'statsmodels/datasets/sunspots/sunspots.csv' adding 'statsmodels/datasets/tests/__init__.py' adding 'statsmodels/datasets/tests/test_data.py' adding 'statsmodels/datasets/tests/test_utils.py' adding 'statsmodels/discrete/__init__.py' adding 'statsmodels/discrete/_diagnostics_count.py' adding 'statsmodels/discrete/conditional_models.py' adding 'statsmodels/discrete/count_model.py' adding 'statsmodels/discrete/diagnostic.py' adding 'statsmodels/discrete/discrete_margins.py' adding 'statsmodels/discrete/discrete_model.py' adding 'statsmodels/discrete/truncated_model.py' adding 'statsmodels/discrete/tests/__init__.py' adding 'statsmodels/discrete/tests/test_conditional.py' adding 'statsmodels/discrete/tests/test_constrained.py' adding 'statsmodels/discrete/tests/test_count_model.py' adding 'statsmodels/discrete/tests/test_diagnostic.py' adding 'statsmodels/discrete/tests/test_discrete.py' adding 'statsmodels/discrete/tests/test_margins.py' adding 'statsmodels/discrete/tests/test_predict.py' adding 'statsmodels/discrete/tests/test_sandwich_cov.py' adding 'statsmodels/discrete/tests/test_truncated_model.py' adding 'statsmodels/discrete/tests/results/__init__.py' adding 'statsmodels/discrete/tests/results/mn_logit_summary.txt' adding 'statsmodels/discrete/tests/results/mnlogit_resid.csv' adding 'statsmodels/discrete/tests/results/nbinom_resids.csv' adding 'statsmodels/discrete/tests/results/phat_mnlogit.csv' adding 'statsmodels/discrete/tests/results/poisson_resid.csv' adding 'statsmodels/discrete/tests/results/predict_prob_poisson.csv' adding 'statsmodels/discrete/tests/results/results_count_margins.py' adding 'statsmodels/discrete/tests/results/results_count_robust_cluster.py' adding 'statsmodels/discrete/tests/results/results_discrete.py' adding 'statsmodels/discrete/tests/results/results_glm_logit_constrained.py' adding 'statsmodels/discrete/tests/results/results_poisson_constrained.py' adding 'statsmodels/discrete/tests/results/results_predict.py' adding 'statsmodels/discrete/tests/results/results_truncated.py' adding 'statsmodels/discrete/tests/results/results_truncated_st.py' adding 'statsmodels/discrete/tests/results/ships.csv' adding 'statsmodels/discrete/tests/results/sm3533.csv' adding 'statsmodels/discrete/tests/results/yhat_mnlogit.csv' adding 'statsmodels/discrete/tests/results/yhat_poisson.csv' adding 'statsmodels/distributions/__init__.py' adding 'statsmodels/distributions/bernstein.py' adding 'statsmodels/distributions/discrete.py' adding 'statsmodels/distributions/edgeworth.py' adding 'statsmodels/distributions/empirical_distribution.py' adding 'statsmodels/distributions/mixture_rvs.py' adding 'statsmodels/distributions/tools.py' adding 'statsmodels/distributions/copula/__init__.py' adding 'statsmodels/distributions/copula/_special.py' adding 'statsmodels/distributions/copula/api.py' adding 'statsmodels/distributions/copula/archimedean.py' adding 'statsmodels/distributions/copula/copulas.py' adding 'statsmodels/distributions/copula/depfunc_ev.py' adding 'statsmodels/distributions/copula/elliptical.py' adding 'statsmodels/distributions/copula/extreme_value.py' adding 'statsmodels/distributions/copula/other_copulas.py' adding 'statsmodels/distributions/copula/transforms.py' adding 'statsmodels/distributions/tests/__init__.py' adding 'statsmodels/distributions/tests/test_bernstein.py' adding 'statsmodels/distributions/tests/test_discrete.py' adding 'statsmodels/distributions/tests/test_ecdf.py' adding 'statsmodels/distributions/tests/test_edgeworth.py' adding 'statsmodels/distributions/tests/test_mixture.py' adding 'statsmodels/distributions/tests/test_tools.py' adding 'statsmodels/duration/__init__.py' adding 'statsmodels/duration/_kernel_estimates.py' adding 'statsmodels/duration/api.py' adding 'statsmodels/duration/hazard_regression.py' adding 'statsmodels/duration/survfunc.py' adding 'statsmodels/duration/tests/__init__.py' adding 'statsmodels/duration/tests/test_phreg.py' adding 'statsmodels/duration/tests/test_survfunc.py' adding 'statsmodels/duration/tests/results/__init__.py' adding 'statsmodels/duration/tests/results/bmt.csv' adding 'statsmodels/duration/tests/results/bmt_results.csv' adding 'statsmodels/duration/tests/results/phreg_gentests.py' adding 'statsmodels/duration/tests/results/survival_data_1000_10.csv' adding 'statsmodels/duration/tests/results/survival_data_100_5.csv' adding 'statsmodels/duration/tests/results/survival_data_20_1.csv' adding 'statsmodels/duration/tests/results/survival_data_50_1.csv' adding 'statsmodels/duration/tests/results/survival_data_50_2.csv' adding 'statsmodels/duration/tests/results/survival_enet_r_results.py' adding 'statsmodels/duration/tests/results/survival_r_results.py' adding 'statsmodels/emplike/__init__.py' adding 'statsmodels/emplike/aft_el.py' adding 'statsmodels/emplike/api.py' adding 'statsmodels/emplike/descriptive.py' adding 'statsmodels/emplike/elanova.py' adding 'statsmodels/emplike/elregress.py' adding 'statsmodels/emplike/originregress.py' adding 'statsmodels/emplike/tests/__init__.py' adding 'statsmodels/emplike/tests/test_aft.py' adding 'statsmodels/emplike/tests/test_anova.py' adding 'statsmodels/emplike/tests/test_descriptive.py' adding 'statsmodels/emplike/tests/test_origin.py' adding 'statsmodels/emplike/tests/test_regression.py' adding 'statsmodels/emplike/tests/results/__init__.py' adding 'statsmodels/emplike/tests/results/el_results.py' adding 'statsmodels/formula/__init__.py' adding 'statsmodels/formula/api.py' adding 'statsmodels/formula/formulatools.py' adding 'statsmodels/formula/tests/__init__.py' adding 'statsmodels/formula/tests/test_formula.py' adding 'statsmodels/gam/__init__.py' adding 'statsmodels/gam/api.py' adding 'statsmodels/gam/gam_penalties.py' adding 'statsmodels/gam/generalized_additive_model.py' adding 'statsmodels/gam/smooth_basis.py' adding 'statsmodels/gam/gam_cross_validation/__init__.py' adding 'statsmodels/gam/gam_cross_validation/cross_validators.py' adding 'statsmodels/gam/gam_cross_validation/gam_cross_validation.py' adding 'statsmodels/gam/tests/__init__.py' adding 'statsmodels/gam/tests/test_gam.py' adding 'statsmodels/gam/tests/test_penalized.py' adding 'statsmodels/gam/tests/test_smooth_basis.py' adding 'statsmodels/gam/tests/results/__init__.py' adding 'statsmodels/gam/tests/results/autos.csv' adding 'statsmodels/gam/tests/results/autos_exog.csv' adding 'statsmodels/gam/tests/results/autos_predict.csv' adding 'statsmodels/gam/tests/results/cubic_cyclic_splines_from_mgcv.csv' adding 'statsmodels/gam/tests/results/gam_PIRLS_results.csv' adding 'statsmodels/gam/tests/results/logit_gam_mgcv.csv' adding 'statsmodels/gam/tests/results/motorcycle.csv' adding 'statsmodels/gam/tests/results/prediction_from_mgcv.csv' adding 'statsmodels/gam/tests/results/results_mpg_bs.py' adding 'statsmodels/gam/tests/results/results_mpg_bs_poisson.py' adding 'statsmodels/gam/tests/results/results_pls.py' adding 'statsmodels/genmod/__init__.py' adding 'statsmodels/genmod/_tweedie_compound_poisson.py' adding 'statsmodels/genmod/api.py' adding 'statsmodels/genmod/bayes_mixed_glm.py' adding 'statsmodels/genmod/cov_struct.py' adding 'statsmodels/genmod/generalized_estimating_equations.py' adding 'statsmodels/genmod/generalized_linear_model.py' adding 'statsmodels/genmod/qif.py' adding 'statsmodels/genmod/families/__init__.py' adding 'statsmodels/genmod/families/family.py' adding 'statsmodels/genmod/families/links.py' adding 'statsmodels/genmod/families/varfuncs.py' adding 'statsmodels/genmod/families/tests/__init__.py' adding 'statsmodels/genmod/families/tests/test_family.py' adding 'statsmodels/genmod/families/tests/test_link.py' adding 'statsmodels/genmod/tests/__init__.py' adding 'statsmodels/genmod/tests/gee_categorical_simulation_check.py' adding 'statsmodels/genmod/tests/gee_gaussian_simulation_check.py' adding 'statsmodels/genmod/tests/gee_poisson_simulation_check.py' adding 'statsmodels/genmod/tests/gee_simulation_check.py' adding 'statsmodels/genmod/tests/test_bayes_mixed_glm.py' adding 'statsmodels/genmod/tests/test_constrained.py' adding 'statsmodels/genmod/tests/test_gee.py' adding 'statsmodels/genmod/tests/test_gee_glm.py' adding 'statsmodels/genmod/tests/test_glm.py' adding 'statsmodels/genmod/tests/test_glm_weights.py' adding 'statsmodels/genmod/tests/test_qif.py' adding 'statsmodels/genmod/tests/test_score_test.py' adding 'statsmodels/genmod/tests/results/__init__.py' adding 'statsmodels/genmod/tests/results/elastic_net_generate_tests.py' adding 'statsmodels/genmod/tests/results/enet_binomial.csv' adding 'statsmodels/genmod/tests/results/enet_poisson.csv' adding 'statsmodels/genmod/tests/results/epil.csv' adding 'statsmodels/genmod/tests/results/gee_generate_tests.py' adding 'statsmodels/genmod/tests/results/gee_linear_1.csv' adding 'statsmodels/genmod/tests/results/gee_logistic_1.csv' adding 'statsmodels/genmod/tests/results/gee_nested_linear_1.csv' adding 'statsmodels/genmod/tests/results/gee_nominal_1.csv' adding 'statsmodels/genmod/tests/results/gee_ordinal_1.csv' adding 'statsmodels/genmod/tests/results/gee_poisson_1.csv' adding 'statsmodels/genmod/tests/results/glm_test_resids.py' adding 'statsmodels/genmod/tests/results/glmnet_r_results.py' adding 'statsmodels/genmod/tests/results/igaussident_resids.csv' adding 'statsmodels/genmod/tests/results/inv_gaussian.csv' adding 'statsmodels/genmod/tests/results/iris.csv' adding 'statsmodels/genmod/tests/results/medparlogresids.csv' adding 'statsmodels/genmod/tests/results/res_R_var_weight.py' adding 'statsmodels/genmod/tests/results/results_glm.py' adding 'statsmodels/genmod/tests/results/results_glm_poisson_weights.py' adding 'statsmodels/genmod/tests/results/results_tweedie_aweights_nonrobust.csv' adding 'statsmodels/genmod/tests/results/stata_cancer_glm.csv' adding 'statsmodels/genmod/tests/results/stata_lbw_glm.csv' adding 'statsmodels/genmod/tests/results/stata_medpar1_glm.csv' adding 'statsmodels/graphics/__init__.py' adding 'statsmodels/graphics/_regressionplots_doc.py' adding 'statsmodels/graphics/agreement.py' adding 'statsmodels/graphics/api.py' adding 'statsmodels/graphics/boxplots.py' adding 'statsmodels/graphics/correlation.py' adding 'statsmodels/graphics/dotplots.py' adding 'statsmodels/graphics/factorplots.py' adding 'statsmodels/graphics/functional.py' adding 'statsmodels/graphics/gofplots.py' adding 'statsmodels/graphics/mosaicplot.py' adding 'statsmodels/graphics/plot_grids.py' adding 'statsmodels/graphics/plottools.py' adding 'statsmodels/graphics/regressionplots.py' adding 'statsmodels/graphics/tsaplots.py' adding 'statsmodels/graphics/tukeyplot.py' adding 'statsmodels/graphics/utils.py' adding 'statsmodels/graphics/tests/__init__.py' adding 'statsmodels/graphics/tests/test_agreement.py' adding 'statsmodels/graphics/tests/test_boxplots.py' adding 'statsmodels/graphics/tests/test_correlation.py' adding 'statsmodels/graphics/tests/test_dotplot.py' adding 'statsmodels/graphics/tests/test_factorplots.py' adding 'statsmodels/graphics/tests/test_functional.py' adding 'statsmodels/graphics/tests/test_gofplots.py' adding 'statsmodels/graphics/tests/test_mosaicplot.py' adding 'statsmodels/graphics/tests/test_regressionplots.py' adding 'statsmodels/graphics/tests/test_tsaplots.py' adding 'statsmodels/imputation/__init__.py' adding 'statsmodels/imputation/bayes_mi.py' adding 'statsmodels/imputation/mice.py' adding 'statsmodels/imputation/ros.py' adding 'statsmodels/imputation/tests/__init__.py' adding 'statsmodels/imputation/tests/test_bayes_mi.py' adding 'statsmodels/imputation/tests/test_mice.py' adding 'statsmodels/imputation/tests/test_ros.py' adding 'statsmodels/interface/__init__.py' adding 'statsmodels/iolib/__init__.py' adding 'statsmodels/iolib/api.py' adding 'statsmodels/iolib/foreign.py' adding 'statsmodels/iolib/openfile.py' adding 'statsmodels/iolib/smpickle.py' adding 'statsmodels/iolib/stata_summary_examples.py' adding 'statsmodels/iolib/summary.py' adding 'statsmodels/iolib/summary2.py' adding 'statsmodels/iolib/table.py' adding 'statsmodels/iolib/tableformatting.py' adding 'statsmodels/iolib/tests/__init__.py' adding 'statsmodels/iolib/tests/test_pickle.py' adding 'statsmodels/iolib/tests/test_summary.py' adding 'statsmodels/iolib/tests/test_summary2.py' adding 'statsmodels/iolib/tests/test_summary_old.py' adding 'statsmodels/iolib/tests/test_table.py' adding 'statsmodels/iolib/tests/test_table_econpy.py' adding 'statsmodels/iolib/tests/results/__init__.py' adding 'statsmodels/iolib/tests/results/data_missing.dta' adding 'statsmodels/iolib/tests/results/macrodata.py' adding 'statsmodels/iolib/tests/results/time_series_examples.dta' adding 'statsmodels/miscmodels/__init__.py' adding 'statsmodels/miscmodels/api.py' adding 'statsmodels/miscmodels/count.py' adding 'statsmodels/miscmodels/nonlinls.py' adding 'statsmodels/miscmodels/ordinal_model.py' adding 'statsmodels/miscmodels/tmodel.py' adding 'statsmodels/miscmodels/try_mlecov.py' adding 'statsmodels/miscmodels/tests/__init__.py' adding 'statsmodels/miscmodels/tests/results_tmodel.py' adding 'statsmodels/miscmodels/tests/test_generic_mle.py' adding 'statsmodels/miscmodels/tests/test_ordinal_model.py' adding 'statsmodels/miscmodels/tests/test_poisson.py' adding 'statsmodels/miscmodels/tests/test_tmodel.py' adding 'statsmodels/miscmodels/tests/results/__init__.py' adding 'statsmodels/miscmodels/tests/results/ologit_ucla.csv' adding 'statsmodels/miscmodels/tests/results/results_ordinal_model.py' adding 'statsmodels/multivariate/__init__.py' adding 'statsmodels/multivariate/api.py' adding 'statsmodels/multivariate/cancorr.py' adding 'statsmodels/multivariate/factor.py' adding 'statsmodels/multivariate/manova.py' adding 'statsmodels/multivariate/multivariate_ols.py' adding 'statsmodels/multivariate/pca.py' adding 'statsmodels/multivariate/plots.py' adding 'statsmodels/multivariate/factor_rotation/__init__.py' adding 'statsmodels/multivariate/factor_rotation/_analytic_rotation.py' adding 'statsmodels/multivariate/factor_rotation/_gpa_rotation.py' adding 'statsmodels/multivariate/factor_rotation/_wrappers.py' adding 'statsmodels/multivariate/factor_rotation/tests/__init__.py' adding 'statsmodels/multivariate/factor_rotation/tests/test_rotation.py' adding 'statsmodels/multivariate/tests/__init__.py' adding 'statsmodels/multivariate/tests/test_cancorr.py' adding 'statsmodels/multivariate/tests/test_factor.py' adding 'statsmodels/multivariate/tests/test_manova.py' adding 'statsmodels/multivariate/tests/test_ml_factor.py' adding 'statsmodels/multivariate/tests/test_multivariate_ols.py' adding 'statsmodels/multivariate/tests/test_pca.py' adding 'statsmodels/multivariate/tests/results/__init__.py' adding 'statsmodels/multivariate/tests/results/datamlw.py' adding 'statsmodels/multivariate/tests/results/factor_data.csv' adding 'statsmodels/multivariate/tests/results/factors_stata.csv' adding 'statsmodels/nonparametric/__init__.py' adding 'statsmodels/nonparametric/_kernel_base.py' adding 'statsmodels/nonparametric/_smoothers_lowess.cpython-313-x86_64-linux-gnu.so' adding 'statsmodels/nonparametric/api.py' adding 'statsmodels/nonparametric/bandwidths.py' adding 'statsmodels/nonparametric/kde.py' adding 'statsmodels/nonparametric/kdetools.py' adding 'statsmodels/nonparametric/kernel_density.py' adding 'statsmodels/nonparametric/kernel_regression.py' adding 'statsmodels/nonparametric/kernels.py' adding 'statsmodels/nonparametric/kernels_asymmetric.py' adding 'statsmodels/nonparametric/linbin.cpython-313-x86_64-linux-gnu.so' adding 'statsmodels/nonparametric/smoothers_lowess.py' adding 'statsmodels/nonparametric/smoothers_lowess_old.py' adding 'statsmodels/nonparametric/tests/__init__.py' adding 'statsmodels/nonparametric/tests/test_asymmetric.py' adding 'statsmodels/nonparametric/tests/test_bandwidths.py' adding 'statsmodels/nonparametric/tests/test_kde.py' adding 'statsmodels/nonparametric/tests/test_kernel_density.py' adding 'statsmodels/nonparametric/tests/test_kernel_regression.py' adding 'statsmodels/nonparametric/tests/test_kernels.py' adding 'statsmodels/nonparametric/tests/test_lowess.py' adding 'statsmodels/nonparametric/tests/results/__init__.py' adding 'statsmodels/nonparametric/tests/results/results_kcde.csv' adding 'statsmodels/nonparametric/tests/results/results_kde.csv' adding 'statsmodels/nonparametric/tests/results/results_kde_fft.csv' adding 'statsmodels/nonparametric/tests/results/results_kde_univ_weights.csv' adding 'statsmodels/nonparametric/tests/results/results_kde_weights.csv' adding 'statsmodels/nonparametric/tests/results/results_kernel_regression.csv' adding 'statsmodels/nonparametric/tests/results/test_lowess_delta.csv' adding 'statsmodels/nonparametric/tests/results/test_lowess_frac.csv' adding 'statsmodels/nonparametric/tests/results/test_lowess_iter.csv' adding 'statsmodels/nonparametric/tests/results/test_lowess_simple.csv' adding 'statsmodels/othermod/__init__.py' adding 'statsmodels/othermod/api.py' adding 'statsmodels/othermod/betareg.py' adding 'statsmodels/othermod/tests/__init__.py' adding 'statsmodels/othermod/tests/test_beta.py' adding 'statsmodels/othermod/tests/results/__init__.py' adding 'statsmodels/othermod/tests/results/foodexpenditure.csv' adding 'statsmodels/othermod/tests/results/methylation-test.csv' adding 'statsmodels/othermod/tests/results/resid_methylation.csv' adding 'statsmodels/othermod/tests/results/results_betareg.py' adding 'statsmodels/regression/__init__.py' adding 'statsmodels/regression/_prediction.py' adding 'statsmodels/regression/_tools.py' adding 'statsmodels/regression/dimred.py' adding 'statsmodels/regression/feasible_gls.py' adding 'statsmodels/regression/linear_model.py' adding 'statsmodels/regression/mixed_linear_model.py' adding 'statsmodels/regression/process_regression.py' adding 'statsmodels/regression/quantile_regression.py' adding 'statsmodels/regression/recursive_ls.py' adding 'statsmodels/regression/rolling.py' adding 'statsmodels/regression/tests/__init__.py' adding 'statsmodels/regression/tests/test_cov.py' adding 'statsmodels/regression/tests/test_dimred.py' adding 'statsmodels/regression/tests/test_glsar_gretl.py' adding 'statsmodels/regression/tests/test_glsar_stata.py' adding 'statsmodels/regression/tests/test_lme.py' adding 'statsmodels/regression/tests/test_predict.py' adding 'statsmodels/regression/tests/test_processreg.py' adding 'statsmodels/regression/tests/test_quantile_regression.py' adding 'statsmodels/regression/tests/test_recursive_ls.py' adding 'statsmodels/regression/tests/test_regression.py' adding 'statsmodels/regression/tests/test_robustcov.py' adding 'statsmodels/regression/tests/test_rolling.py' adding 'statsmodels/regression/tests/test_theil.py' adding 'statsmodels/regression/tests/test_tools.py' adding 'statsmodels/regression/tests/results/__init__.py' adding 'statsmodels/regression/tests/results/dietox.csv' adding 'statsmodels/regression/tests/results/generate_lasso.py' adding 'statsmodels/regression/tests/results/generate_lme.py' adding 'statsmodels/regression/tests/results/glmnet_r_results.py' adding 'statsmodels/regression/tests/results/lasso_data.csv' adding 'statsmodels/regression/tests/results/leverage_influence_ols_nostars.txt' adding 'statsmodels/regression/tests/results/lme00.csv' adding 'statsmodels/regression/tests/results/lme01.csv' adding 'statsmodels/regression/tests/results/lme02.csv' adding 'statsmodels/regression/tests/results/lme03.csv' adding 'statsmodels/regression/tests/results/lme04.csv' adding 'statsmodels/regression/tests/results/lme05.csv' adding 'statsmodels/regression/tests/results/lme06.csv' adding 'statsmodels/regression/tests/results/lme07.csv' adding 'statsmodels/regression/tests/results/lme08.csv' adding 'statsmodels/regression/tests/results/lme09.csv' adding 'statsmodels/regression/tests/results/lme10.csv' adding 'statsmodels/regression/tests/results/lme11.csv' adding 'statsmodels/regression/tests/results/lme_r_results.py' adding 'statsmodels/regression/tests/results/macro_gr_corc_stata.py' adding 'statsmodels/regression/tests/results/pastes.csv' adding 'statsmodels/regression/tests/results/results_grunfeld_ols_robust_cluster.py' adding 'statsmodels/regression/tests/results/results_macro_ols_robust.py' adding 'statsmodels/regression/tests/results/results_quantile_regression.py' adding 'statsmodels/regression/tests/results/results_regression.py' adding 'statsmodels/regression/tests/results/results_rls_R.csv' adding 'statsmodels/regression/tests/results/results_rls_stata.csv' adding 'statsmodels/regression/tests/results/results_theil_textile.py' adding 'statsmodels/regression/tests/results/theil_textile_predict.csv' adding 'statsmodels/robust/__init__.py' adding 'statsmodels/robust/_qn.cpython-313-x86_64-linux-gnu.so' adding 'statsmodels/robust/norms.py' adding 'statsmodels/robust/robust_linear_model.py' adding 'statsmodels/robust/scale.py' adding 'statsmodels/robust/tests/__init__.py' adding 'statsmodels/robust/tests/test_mquantiles.py' adding 'statsmodels/robust/tests/test_norms.py' adding 'statsmodels/robust/tests/test_rlm.py' adding 'statsmodels/robust/tests/test_scale.py' adding 'statsmodels/robust/tests/results/__init__.py' adding 'statsmodels/robust/tests/results/results_norms.py' adding 'statsmodels/robust/tests/results/results_rlm.py' adding 'statsmodels/sandbox/__init__.py' adding 'statsmodels/sandbox/bspline.py' adding 'statsmodels/sandbox/descstats.py' adding 'statsmodels/sandbox/gam.py' adding 'statsmodels/sandbox/infotheo.py' adding 'statsmodels/sandbox/mle.py' adding 'statsmodels/sandbox/multilinear.py' adding 'statsmodels/sandbox/pca.py' adding 'statsmodels/sandbox/predict_functional.py' adding 'statsmodels/sandbox/rls.py' adding 'statsmodels/sandbox/sysreg.py' adding 'statsmodels/sandbox/archive/__init__.py' adding 'statsmodels/sandbox/archive/linalg_covmat.py' adding 'statsmodels/sandbox/archive/linalg_decomp_1.py' adding 'statsmodels/sandbox/archive/tsa.py' adding 'statsmodels/sandbox/datarich/__init__.py' adding 'statsmodels/sandbox/datarich/factormodels.py' adding 'statsmodels/sandbox/distributions/__init__.py' adding 'statsmodels/sandbox/distributions/estimators.py' adding 'statsmodels/sandbox/distributions/extras.py' adding 'statsmodels/sandbox/distributions/genpareto.py' adding 'statsmodels/sandbox/distributions/gof_new.py' adding 'statsmodels/sandbox/distributions/multivariate.py' adding 'statsmodels/sandbox/distributions/mv_measures.py' adding 'statsmodels/sandbox/distributions/mv_normal.py' adding 'statsmodels/sandbox/distributions/otherdist.py' adding 'statsmodels/sandbox/distributions/quantize.py' adding 'statsmodels/sandbox/distributions/sppatch.py' adding 'statsmodels/sandbox/distributions/transform_functions.py' adding 'statsmodels/sandbox/distributions/transformed.py' adding 'statsmodels/sandbox/distributions/try_max.py' adding 'statsmodels/sandbox/distributions/try_pot.py' adding 'statsmodels/sandbox/distributions/examples/__init__.py' adding 'statsmodels/sandbox/distributions/examples/ex_extras.py' adding 'statsmodels/sandbox/distributions/examples/ex_fitfr.py' adding 'statsmodels/sandbox/distributions/examples/ex_gof.py' adding 'statsmodels/sandbox/distributions/examples/ex_mvelliptical.py' adding 'statsmodels/sandbox/distributions/examples/ex_transf2.py' adding 'statsmodels/sandbox/distributions/examples/matchdist.py' adding 'statsmodels/sandbox/distributions/tests/__init__.py' adding 'statsmodels/sandbox/distributions/tests/_est_fit.py' adding 'statsmodels/sandbox/distributions/tests/check_moments.py' adding 'statsmodels/sandbox/distributions/tests/distparams.py' adding 'statsmodels/sandbox/distributions/tests/test_extras.py' adding 'statsmodels/sandbox/distributions/tests/test_gof_new.py' adding 'statsmodels/sandbox/distributions/tests/test_multivariate.py' adding 'statsmodels/sandbox/distributions/tests/test_norm_expan.py' adding 'statsmodels/sandbox/distributions/tests/test_transf.py' adding 'statsmodels/sandbox/mcevaluate/__init__.py' adding 'statsmodels/sandbox/mcevaluate/arma.py' adding 'statsmodels/sandbox/nonparametric/__init__.py' adding 'statsmodels/sandbox/nonparametric/densityorthopoly.py' adding 'statsmodels/sandbox/nonparametric/dgp_examples.py' adding 'statsmodels/sandbox/nonparametric/kde2.py' adding 'statsmodels/sandbox/nonparametric/kdecovclass.py' adding 'statsmodels/sandbox/nonparametric/kernel_extras.py' adding 'statsmodels/sandbox/nonparametric/kernels.py' adding 'statsmodels/sandbox/nonparametric/smoothers.py' adding 'statsmodels/sandbox/nonparametric/testdata.py' adding 'statsmodels/sandbox/nonparametric/tests/__init__.py' adding 'statsmodels/sandbox/nonparametric/tests/ex_gam_am_new.py' adding 'statsmodels/sandbox/nonparametric/tests/ex_gam_new.py' adding 'statsmodels/sandbox/nonparametric/tests/ex_smoothers.py' adding 'statsmodels/sandbox/nonparametric/tests/test_kernel_extras.py' adding 'statsmodels/sandbox/nonparametric/tests/test_smoothers.py' adding 'statsmodels/sandbox/panel/__init__.py' adding 'statsmodels/sandbox/panel/correlation_structures.py' adding 'statsmodels/sandbox/panel/mixed.py' adding 'statsmodels/sandbox/panel/panel_short.py' adding 'statsmodels/sandbox/panel/panelmod.py' adding 'statsmodels/sandbox/panel/random_panel.py' adding 'statsmodels/sandbox/panel/sandwich_covariance_generic.py' adding 'statsmodels/sandbox/panel/tests/__init__.py' adding 'statsmodels/sandbox/panel/tests/test_random_panel.py' adding 'statsmodels/sandbox/regression/__init__.py' adding 'statsmodels/sandbox/regression/anova_nistcertified.py' adding 'statsmodels/sandbox/regression/ar_panel.py' adding 'statsmodels/sandbox/regression/example_kernridge.py' adding 'statsmodels/sandbox/regression/gmm.py' adding 'statsmodels/sandbox/regression/kernridgeregress_class.py' adding 'statsmodels/sandbox/regression/ols_anova_original.py' adding 'statsmodels/sandbox/regression/onewaygls.py' adding 'statsmodels/sandbox/regression/penalized.py' adding 'statsmodels/sandbox/regression/predstd.py' adding 'statsmodels/sandbox/regression/runmnl.py' adding 'statsmodels/sandbox/regression/sympy_diff.py' adding 'statsmodels/sandbox/regression/tools.py' adding 'statsmodels/sandbox/regression/treewalkerclass.py' adding 'statsmodels/sandbox/regression/try_catdata.py' adding 'statsmodels/sandbox/regression/try_ols_anova.py' adding 'statsmodels/sandbox/regression/try_treewalker.py' adding 'statsmodels/sandbox/regression/tests/__init__.py' adding 'statsmodels/sandbox/regression/tests/griliches76.dta' adding 'statsmodels/sandbox/regression/tests/racd10data_with_transformed.csv' adding 'statsmodels/sandbox/regression/tests/results_gmm_griliches.py' adding 'statsmodels/sandbox/regression/tests/results_gmm_griliches_iter.py' adding 'statsmodels/sandbox/regression/tests/results_gmm_poisson.py' adding 'statsmodels/sandbox/regression/tests/results_ivreg2_griliches.py' adding 'statsmodels/sandbox/regression/tests/test_gmm.py' adding 'statsmodels/sandbox/regression/tests/test_gmm_poisson.py' adding 'statsmodels/sandbox/stats/__init__.py' adding 'statsmodels/sandbox/stats/contrast_tools.py' adding 'statsmodels/sandbox/stats/diagnostic.py' adding 'statsmodels/sandbox/stats/ex_newtests.py' adding 'statsmodels/sandbox/stats/multicomp.py' adding 'statsmodels/sandbox/stats/runs.py' adding 'statsmodels/sandbox/stats/stats_dhuard.py' adding 'statsmodels/sandbox/stats/stats_mstats_short.py' adding 'statsmodels/sandbox/stats/tests/__init__.py' adding 'statsmodels/sandbox/stats/tests/test_multicomp.py' adding 'statsmodels/sandbox/stats/tests/test_runs.py' adding 'statsmodels/sandbox/tests/__init__.py' adding 'statsmodels/sandbox/tests/maketests_mlabwrap.py' adding 'statsmodels/sandbox/tests/savervs.py' adding 'statsmodels/sandbox/tests/test_gam.py' adding 'statsmodels/sandbox/tests/test_pca.py' adding 'statsmodels/sandbox/tests/test_predict_functional.py' adding 'statsmodels/sandbox/tools/__init__.py' adding 'statsmodels/sandbox/tools/cross_val.py' adding 'statsmodels/sandbox/tools/mctools.py' adding 'statsmodels/sandbox/tools/tools_pca.py' adding 'statsmodels/sandbox/tools/try_mctools.py' adding 'statsmodels/sandbox/tsa/__init__.py' adding 'statsmodels/sandbox/tsa/diffusion.py' adding 'statsmodels/sandbox/tsa/diffusion2.py' adding 'statsmodels/sandbox/tsa/example_arma.py' adding 'statsmodels/sandbox/tsa/fftarma.py' adding 'statsmodels/sandbox/tsa/movstat.py' adding 'statsmodels/sandbox/tsa/try_arma_more.py' adding 'statsmodels/sandbox/tsa/try_fi.py' adding 'statsmodels/sandbox/tsa/try_var_convolve.py' adding 'statsmodels/sandbox/tsa/varma.py' adding 'statsmodels/src/__init__.py' adding 'statsmodels/stats/__init__.py' adding 'statsmodels/stats/_adnorm.py' adding 'statsmodels/stats/_delta_method.py' adding 'statsmodels/stats/_diagnostic_other.py' adding 'statsmodels/stats/_inference_tools.py' adding 'statsmodels/stats/_knockoff.py' adding 'statsmodels/stats/_lilliefors.py' adding 'statsmodels/stats/_lilliefors_critical_values.py' adding 'statsmodels/stats/anova.py' adding 'statsmodels/stats/api.py' adding 'statsmodels/stats/base.py' adding 'statsmodels/stats/contingency_tables.py' adding 'statsmodels/stats/contrast.py' adding 'statsmodels/stats/correlation_tools.py' adding 'statsmodels/stats/descriptivestats.py' adding 'statsmodels/stats/diagnostic.py' adding 'statsmodels/stats/diagnostic_gen.py' adding 'statsmodels/stats/dist_dependence_measures.py' adding 'statsmodels/stats/effect_size.py' adding 'statsmodels/stats/gof.py' adding 'statsmodels/stats/inter_rater.py' adding 'statsmodels/stats/knockoff_regeffects.py' adding 'statsmodels/stats/mediation.py' adding 'statsmodels/stats/meta_analysis.py' adding 'statsmodels/stats/moment_helpers.py' adding 'statsmodels/stats/multicomp.py' adding 'statsmodels/stats/multitest.py' adding 'statsmodels/stats/multivariate.py' adding 'statsmodels/stats/multivariate_tools.py' adding 'statsmodels/stats/nonparametric.py' adding 'statsmodels/stats/oaxaca.py' adding 'statsmodels/stats/oneway.py' adding 'statsmodels/stats/outliers_influence.py' adding 'statsmodels/stats/power.py' adding 'statsmodels/stats/proportion.py' adding 'statsmodels/stats/rates.py' adding 'statsmodels/stats/regularized_covariance.py' adding 'statsmodels/stats/robust_compare.py' adding 'statsmodels/stats/sandwich_covariance.py' adding 'statsmodels/stats/stattools.py' adding 'statsmodels/stats/tabledist.py' adding 'statsmodels/stats/weightstats.py' adding 'statsmodels/stats/libqsturng/CH.r' adding 'statsmodels/stats/libqsturng/LICENSE.txt' adding 'statsmodels/stats/libqsturng/__init__.py' adding 'statsmodels/stats/libqsturng/make_tbls.py' adding 'statsmodels/stats/libqsturng/qsturng_.py' adding 'statsmodels/stats/libqsturng/tests/__init__.py' adding 'statsmodels/stats/libqsturng/tests/bootleg.dat' adding 'statsmodels/stats/libqsturng/tests/test_qsturng.py' adding 'statsmodels/stats/tests/__init__.py' adding 'statsmodels/stats/tests/test_anova.py' adding 'statsmodels/stats/tests/test_anova_rm.py' adding 'statsmodels/stats/tests/test_base.py' adding 'statsmodels/stats/tests/test_contingency_tables.py' adding 'statsmodels/stats/tests/test_contrast.py' adding 'statsmodels/stats/tests/test_correlation.py' adding 'statsmodels/stats/tests/test_corrpsd.py' adding 'statsmodels/stats/tests/test_data.txt' adding 'statsmodels/stats/tests/test_deltacov.py' adding 'statsmodels/stats/tests/test_descriptivestats.py' adding 'statsmodels/stats/tests/test_diagnostic.py' adding 'statsmodels/stats/tests/test_diagnostic_other.py' adding 'statsmodels/stats/tests/test_dist_dependant_measures.py' adding 'statsmodels/stats/tests/test_effectsize.py' adding 'statsmodels/stats/tests/test_gof.py' adding 'statsmodels/stats/tests/test_groups_sw.py' adding 'statsmodels/stats/tests/test_influence.py' adding 'statsmodels/stats/tests/test_inter_rater.py' adding 'statsmodels/stats/tests/test_knockoff.py' adding 'statsmodels/stats/tests/test_lilliefors.py' adding 'statsmodels/stats/tests/test_mediation.py' adding 'statsmodels/stats/tests/test_meta.py' adding 'statsmodels/stats/tests/test_moment_helpers.py' adding 'statsmodels/stats/tests/test_multi.py' adding 'statsmodels/stats/tests/test_multivariate.py' adding 'statsmodels/stats/tests/test_nonparametric.py' adding 'statsmodels/stats/tests/test_oaxaca.py' adding 'statsmodels/stats/tests/test_oneway.py' adding 'statsmodels/stats/tests/test_outliers_influence.py' adding 'statsmodels/stats/tests/test_pairwise.py' adding 'statsmodels/stats/tests/test_panel_robustcov.py' adding 'statsmodels/stats/tests/test_power.py' adding 'statsmodels/stats/tests/test_proportion.py' adding 'statsmodels/stats/tests/test_qsturng.py' adding 'statsmodels/stats/tests/test_rates_poisson.py' adding 'statsmodels/stats/tests/test_regularized_covariance.py' adding 'statsmodels/stats/tests/test_robust_compare.py' adding 'statsmodels/stats/tests/test_sandwich.py' adding 'statsmodels/stats/tests/test_statstools.py' adding 'statsmodels/stats/tests/test_tabledist.py' adding 'statsmodels/stats/tests/test_tost.py' adding 'statsmodels/stats/tests/test_weightstats.py' adding 'statsmodels/stats/tests/results/__init__.py' adding 'statsmodels/stats/tests/results/binary_constrict.csv' adding 'statsmodels/stats/tests/results/bootleg.csv' adding 'statsmodels/stats/tests/results/contingency_table_r_results.csv' adding 'statsmodels/stats/tests/results/data.dat' adding 'statsmodels/stats/tests/results/framing.csv' adding 'statsmodels/stats/tests/results/influence_lsdiag_R.json' adding 'statsmodels/stats/tests/results/influence_measures_R.csv' adding 'statsmodels/stats/tests/results/influence_measures_bool_R.csv' adding 'statsmodels/stats/tests/results/lilliefors_critical_value_simulation.py' adding 'statsmodels/stats/tests/results/results_influence_logit.csv' adding 'statsmodels/stats/tests/results/results_meta.py' adding 'statsmodels/stats/tests/results/results_multinomial_proportions.py' adding 'statsmodels/stats/tests/results/results_panelrobust.py' adding 'statsmodels/stats/tests/results/results_power.py' adding 'statsmodels/stats/tests/results/results_proportion.py' adding 'statsmodels/stats/tests/results/results_rates.py' adding 'statsmodels/stats/tests/results/wspec1.csv' adding 'statsmodels/stats/tests/results/wspec2.csv' adding 'statsmodels/stats/tests/results/wspec3.csv' adding 'statsmodels/stats/tests/results/wspec4.csv' adding 'statsmodels/tests/__init__.py' adding 'statsmodels/tests/test_package.py' adding 'statsmodels/tests/test_x13.py' adding 'statsmodels/tools/__init__.py' adding 'statsmodels/tools/_test_runner.py' adding 'statsmodels/tools/_testing.py' adding 'statsmodels/tools/catadd.py' adding 'statsmodels/tools/data.py' adding 'statsmodels/tools/decorators.py' adding 'statsmodels/tools/docstring.py' adding 'statsmodels/tools/eval_measures.py' adding 'statsmodels/tools/grouputils.py' adding 'statsmodels/tools/linalg.py' adding 'statsmodels/tools/numdiff.py' adding 'statsmodels/tools/parallel.py' adding 'statsmodels/tools/print_version.py' adding 'statsmodels/tools/rng_qrng.py' adding 'statsmodels/tools/rootfinding.py' adding 'statsmodels/tools/sequences.py' adding 'statsmodels/tools/sm_exceptions.py' adding 'statsmodels/tools/testing.py' adding 'statsmodels/tools/tools.py' adding 'statsmodels/tools/transform_model.py' adding 'statsmodels/tools/typing.py' adding 'statsmodels/tools/web.py' adding 'statsmodels/tools/tests/__init__.py' adding 'statsmodels/tools/tests/test_catadd.py' adding 'statsmodels/tools/tests/test_data.py' adding 'statsmodels/tools/tests/test_decorators.py' adding 'statsmodels/tools/tests/test_docstring.py' adding 'statsmodels/tools/tests/test_eval_measures.py' adding 'statsmodels/tools/tests/test_grouputils.py' adding 'statsmodels/tools/tests/test_linalg.py' adding 'statsmodels/tools/tests/test_numdiff.py' adding 'statsmodels/tools/tests/test_parallel.py' adding 'statsmodels/tools/tests/test_rootfinding.py' adding 'statsmodels/tools/tests/test_sequences.py' adding 'statsmodels/tools/tests/test_testing.py' adding 'statsmodels/tools/tests/test_tools.py' adding 'statsmodels/tools/tests/test_transform_model.py' adding 'statsmodels/tools/tests/test_web.py' adding 'statsmodels/tools/validation/__init__.py' adding 'statsmodels/tools/validation/decorators.py' adding 'statsmodels/tools/validation/validation.py' adding 'statsmodels/tools/validation/tests/__init__.py' adding 'statsmodels/tools/validation/tests/test_validation.py' adding 'statsmodels/treatment/__init__.py' adding 'statsmodels/treatment/treatment_effects.py' adding 'statsmodels/treatment/tests/__init__.py' adding 'statsmodels/treatment/tests/test_teffects.py' adding 'statsmodels/treatment/tests/results/__init__.py' adding 'statsmodels/treatment/tests/results/cataneo2.csv' adding 'statsmodels/treatment/tests/results/results_teffects.py' adding 'statsmodels/tsa/__init__.py' adding 'statsmodels/tsa/_bds.py' adding 'statsmodels/tsa/_innovations.cpython-313-x86_64-linux-gnu.so' adding 'statsmodels/tsa/adfvalues.py' adding 'statsmodels/tsa/api.py' adding 'statsmodels/tsa/ar_model.py' adding 'statsmodels/tsa/arima_model.py' adding 'statsmodels/tsa/arima_process.py' adding 'statsmodels/tsa/arma_mle.py' adding 'statsmodels/tsa/coint_tables.py' adding 'statsmodels/tsa/descriptivestats.py' adding 'statsmodels/tsa/deterministic.py' adding 'statsmodels/tsa/mlemodel.py' adding 'statsmodels/tsa/seasonal.py' adding 'statsmodels/tsa/stattools.py' adding 'statsmodels/tsa/tsatools.py' adding 'statsmodels/tsa/varma_process.py' adding 'statsmodels/tsa/x13.py' adding 'statsmodels/tsa/ardl/__init__.py' adding 'statsmodels/tsa/ardl/model.py' adding 'statsmodels/tsa/ardl/pss_critical_values.py' adding 'statsmodels/tsa/ardl/_pss_critical_values/__init__.py' adding 'statsmodels/tsa/ardl/_pss_critical_values/pss-process.py' adding 'statsmodels/tsa/ardl/_pss_critical_values/pss.py' adding 'statsmodels/tsa/ardl/tests/__init__.py' adding 'statsmodels/tsa/ardl/tests/test_ardl.py' adding 'statsmodels/tsa/arima/__init__.py' adding 'statsmodels/tsa/arima/api.py' adding 'statsmodels/tsa/arima/model.py' adding 'statsmodels/tsa/arima/params.py' adding 'statsmodels/tsa/arima/specification.py' adding 'statsmodels/tsa/arima/tools.py' adding 'statsmodels/tsa/arima/datasets/__init__.py' adding 'statsmodels/tsa/arima/datasets/brockwell_davis_2002/__init__.py' adding 'statsmodels/tsa/arima/datasets/brockwell_davis_2002/data/__init__.py' adding 'statsmodels/tsa/arima/datasets/brockwell_davis_2002/data/dowj.py' adding 'statsmodels/tsa/arima/datasets/brockwell_davis_2002/data/lake.py' adding 'statsmodels/tsa/arima/datasets/brockwell_davis_2002/data/oshorts.py' adding 'statsmodels/tsa/arima/datasets/brockwell_davis_2002/data/sbl.py' adding 'statsmodels/tsa/arima/estimators/__init__.py' adding 'statsmodels/tsa/arima/estimators/burg.py' adding 'statsmodels/tsa/arima/estimators/durbin_levinson.py' adding 'statsmodels/tsa/arima/estimators/gls.py' adding 'statsmodels/tsa/arima/estimators/hannan_rissanen.py' adding 'statsmodels/tsa/arima/estimators/innovations.py' adding 'statsmodels/tsa/arima/estimators/statespace.py' adding 'statsmodels/tsa/arima/estimators/yule_walker.py' adding 'statsmodels/tsa/arima/estimators/tests/__init__.py' adding 'statsmodels/tsa/arima/estimators/tests/test_burg.py' adding 'statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py' adding 'statsmodels/tsa/arima/estimators/tests/test_gls.py' adding 'statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py' adding 'statsmodels/tsa/arima/estimators/tests/test_innovations.py' adding 'statsmodels/tsa/arima/estimators/tests/test_statespace.py' adding 'statsmodels/tsa/arima/estimators/tests/test_yule_walker.py' adding 'statsmodels/tsa/arima/tests/__init__.py' adding 'statsmodels/tsa/arima/tests/test_model.py' adding 'statsmodels/tsa/arima/tests/test_params.py' adding 'statsmodels/tsa/arima/tests/test_specification.py' adding 'statsmodels/tsa/arima/tests/test_tools.py' adding 'statsmodels/tsa/base/__init__.py' adding 'statsmodels/tsa/base/datetools.py' adding 'statsmodels/tsa/base/prediction.py' adding 'statsmodels/tsa/base/tsa_model.py' adding 'statsmodels/tsa/base/tests/__init__.py' adding 'statsmodels/tsa/base/tests/test_base.py' adding 'statsmodels/tsa/base/tests/test_datetools.py' adding 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'statsmodels/tsa/tests/results/results_arima_forecasts_all_mle_diff.csv' adding 'statsmodels/tsa/tests/results/results_arma.py' adding 'statsmodels/tsa/tests/results/results_arma_acf.py' adding 'statsmodels/tsa/tests/results/results_arma_forecasts.csv' adding 'statsmodels/tsa/tests/results/results_ccf.csv' adding 'statsmodels/tsa/tests/results/results_corrgram.csv' adding 'statsmodels/tsa/tests/results/results_process.py' adding 'statsmodels/tsa/tests/results/rgnp.csv' adding 'statsmodels/tsa/tests/results/rgnpq.csv' adding 'statsmodels/tsa/tests/results/savedrvs.py' adding 'statsmodels/tsa/tests/results/stkprc.csv' adding 'statsmodels/tsa/tests/results/y_arma_data.csv' adding 'statsmodels/tsa/tests/results/yhat_css_c.csv' adding 'statsmodels/tsa/tests/results/yhat_css_nc.csv' adding 'statsmodels/tsa/tests/results/yhat_exact_c.csv' adding 'statsmodels/tsa/tests/results/yhat_exact_nc.csv' adding 'statsmodels/tsa/vector_ar/__init__.py' adding 'statsmodels/tsa/vector_ar/api.py' adding 'statsmodels/tsa/vector_ar/hypothesis_test_results.py' adding 'statsmodels/tsa/vector_ar/irf.py' adding 'statsmodels/tsa/vector_ar/output.py' adding 'statsmodels/tsa/vector_ar/plotting.py' adding 'statsmodels/tsa/vector_ar/svar_model.py' adding 'statsmodels/tsa/vector_ar/util.py' adding 'statsmodels/tsa/vector_ar/var_model.py' adding 'statsmodels/tsa/vector_ar/vecm.py' adding 'statsmodels/tsa/vector_ar/tests/__init__.py' adding 'statsmodels/tsa/vector_ar/tests/example_svar.py' adding 'statsmodels/tsa/vector_ar/tests/test_coint.py' adding 'statsmodels/tsa/vector_ar/tests/test_svar.py' adding 'statsmodels/tsa/vector_ar/tests/test_var.py' adding 'statsmodels/tsa/vector_ar/tests/test_var_jmulti.py' adding 'statsmodels/tsa/vector_ar/tests/test_vecm.py' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/__init__.py' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_Sigmau.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_diag.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_fc5.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realcons.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realcons_realgdp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realcons_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realgdp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realgdp_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_granger_causality_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_ir.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_c_lagorder.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_Sigmau.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_diag.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_fc5.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realcons.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realcons_realgdp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realcons_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realgdp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realgdp_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_granger_causality_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_ir.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cs_lagorder.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_Sigmau.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_diag.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_fc5.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realcons.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realcons_realgdp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realcons_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realgdp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realgdp_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_granger_causality_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_ir.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_cst_lagorder.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_Sigmau.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_diag.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_fc5.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realcons.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realcons_realgdp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realcons_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realgdp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realgdp_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_granger_causality_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_ir.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ct_lagorder.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_Sigmau.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_diag.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_fc5.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realcons.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realcons_realgdp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realcons_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realgdp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realgdp_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_granger_causality_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_ir.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_nc_lagorder.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_Sigmau.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_diag.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_fc5.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realcons.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realcons_realgdp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realcons_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realgdp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realgdp_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_granger_causality_realinv.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_ir.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/macrodata_jmulti_ncs_lagorder.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/parse_jmulti_var_output.py' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/parse_jmulti_vecm_output.py' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_Sigmau.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_diag.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_fc5.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_granger_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_granger_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_inst_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_inst_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_ir.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ci_lagorder.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_Sigmau.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_diag.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_fc5.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_granger_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_granger_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_inst_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_inst_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_ir.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cili_lagorder.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_Sigmau.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_diag.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_fc5.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_granger_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_granger_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_inst_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_inst_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_ir.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cis_lagorder.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_Sigmau.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_diag.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_fc5.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_granger_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_granger_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_inst_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_inst_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_ir.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cisli_lagorder.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_Sigmau.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_diag.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_fc5.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_granger_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_granger_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_inst_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_inst_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_ir.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_co_lagorder.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_Sigmau.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_diag.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_fc5.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_granger_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_granger_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_inst_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_inst_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_ir.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_colo_lagorder.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_Sigmau.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_diag.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_fc5.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_granger_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_granger_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_inst_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_inst_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_ir.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_cos_lagorder.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_Sigmau.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_diag.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_fc5.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_granger_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_granger_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_inst_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_inst_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_ir.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_coslo_lagorder.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_Sigmau.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_diag.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_fc5.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_granger_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_granger_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_inst_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_inst_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_ir.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_nc_lagorder.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_Sigmau.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_diag.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_fc5.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_granger_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_granger_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_inst_causality_dp_r.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_inst_causality_r_dp.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_ir.txt' adding 'statsmodels/tsa/vector_ar/tests/JMulTi_results/vecm_e6_jmulti_ncs_lagorder.txt' adding 'statsmodels/tsa/vector_ar/tests/Matlab_results/__init__.py' adding 'statsmodels/tsa/vector_ar/tests/Matlab_results/test_coint.csv' adding 'statsmodels/tsa/vector_ar/tests/results/__init__.py' adding 'statsmodels/tsa/vector_ar/tests/results/e1.dat' adding 'statsmodels/tsa/vector_ar/tests/results/e2.dat' adding 'statsmodels/tsa/vector_ar/tests/results/e3.dat' adding 'statsmodels/tsa/vector_ar/tests/results/e4.dat' adding 'statsmodels/tsa/vector_ar/tests/results/e5.dat' adding 'statsmodels/tsa/vector_ar/tests/results/e6.dat' adding 'statsmodels/tsa/vector_ar/tests/results/results_svar.py' adding 'statsmodels/tsa/vector_ar/tests/results/results_svar_st.py' adding 'statsmodels/tsa/vector_ar/tests/results/results_var.py' adding 'statsmodels/tsa/vector_ar/tests/results/results_var_data.py' adding 'statsmodels/tsa/vector_ar/tests/results/vars_results.npz' adding 'statsmodels-0.14.5+dfsg.dist-info/licenses/LICENSE.txt' adding 'statsmodels-0.14.5+dfsg.dist-info/METADATA' adding 'statsmodels-0.14.5+dfsg.dist-info/WHEEL' adding 'statsmodels-0.14.5+dfsg.dist-info/top_level.txt' adding 'statsmodels-0.14.5+dfsg.dist-info/RECORD' removing build/bdist.linux-x86_64/wheel Successfully built statsmodels-0.14.5+dfsg-cp313-cp313-linux_x86_64.whl I: pybuild plugin_pyproject:144: Unpacking wheel built for python3.13 with "installer" module debian/rules execute_after_dh_auto_build-indep make[1]: Entering directory '/build/reproducible-path/statsmodels-0.14.5+dfsg' : # I: Generate documentation : # Build Documentation -- assure existence of build/html for nodoc : # Reproducibility: stopping the clock (or slowing it down enough to get all 00:00:00) with faketime (near-)hangs : # 0.9.0 including notebooks step: in glm_weights.ipynb : # 0.14.5 sphinx-build only: in reading sources, last line output is statsmodels.functional.graphics.hdrboxplot mkdir -p build/html python3 debian/datasets/prepopulate_cache.py ./lme4/InstEval.html ./lme4/Dyestuff2.html ./lme4/Penicillin.html ./lme4/cake.html ./lme4/cbpp.html ./lme4/Pastes.html ./lme4/Arabidopsis.html ./lme4/VerbAgg.html ./lme4/grouseticks.html ./lme4/Dyestuff.html ./lme4/sleepstudy.html ./HistData/gfrance85.html ./HistData/Guerry.html ./HistData/propensity.html ./HistData/Angeville.html ./HistData/gfrance.html ./vcd/BrokenMarriage.html ./vcd/Saxony.html ./vcd/OvaryCancer.html ./vcd/Federalist.html ./vcd/Hospital.html ./vcd/Hitters.html ./vcd/RepVict.html ./vcd/JointSports.html ./vcd/Butterfly.html ./vcd/WeldonDice.html ./vcd/NonResponse.html ./vcd/Rochdale.html ./vcd/Baseball.html ./vcd/VisualAcuity.html ./vcd/Lifeboats.html ./vcd/Arthritis.html ./vcd/DanishWelfare.html ./vcd/MSPatients.html ./vcd/Employment.html ./vcd/SpaceShuttle.html ./vcd/SexualFun.html ./vcd/WomenQueue.html ./vcd/CoalMiners.html ./vcd/Suicide.html ./vcd/UKSoccer.html ./vcd/Bundesliga.html ./vcd/Punishment.html ./vcd/PreSex.html ./vcd/HorseKicks.html ./vcd/JobSatisfaction.html ./vcd/Trucks.html ./vcd/VonBort.html ./vcd/Bundestag2005.html ./geepack/muscatine.html ./geepack/dietox.html ./geepack/sitka89.html ./geepack/spruce.html ./geepack/koch.html ./geepack/seizure.html ./geepack/respiratory.html ./geepack/respdis.html ./geepack/ohio.html ./lattice/USMortality.html ./lattice/barley.html ./lattice/environmental.html ./lattice/ethanol.html ./lattice/USRegionalMortality.html ./lattice/melanoma.html ./lattice/singer.html ./carData/Friendly.html ./carData/Highway1.html ./carData/Blackmore.html ./carData/Bfox.html ./carData/WeightLoss.html ./carData/UN.html ./carData/AMSsurvey.html ./carData/Moore.html ./carData/KosteckiDillon.html ./carData/Mandel.html ./carData/Ginzberg.html ./carData/Guyer.html ./carData/Salaries.html ./carData/SLID.html ./carData/Wool.html ./carData/WVS.html ./carData/Hartnagel.html ./carData/GSSvocab.html ./carData/Womenlf.html ./carData/Rossi.html ./carData/Pottery.html ./carData/Arrests.html ./carData/Greene.html ./carData/Ornstein.html ./carData/UN98.html ./carData/Davis.html ./carData/USPop.html ./carData/Freedman.html ./carData/OBrienKaiserLong.html ./carData/Wong.html ./carData/LoBD.html ./carData/MplsDemo.html ./carData/DavisThin.html ./carData/Adler.html ./carData/Sahlins.html ./carData/Transact.html ./carData/CanPop.html ./carData/Soils.html ./carData/Robey.html ./carData/Vocab.html ./carData/OBrienKaiser.html ./carData/Cowles.html ./carData/Duncan.html ./carData/Chile.html ./carData/TitanicSurvival.html ./carData/MplsStops.html ./carData/Prestige.html ./carData/Wells.html ./carData/Florida.html ./carData/Anscombe.html ./carData/Leinhardt.html ./carData/Quartet.html ./carData/Depredations.html ./carData/Burt.html ./carData/BEPS.html ./carData/CES11.html ./carData/Migration.html ./carData/Mroz.html ./carData/Ericksen.html ./carData/States.html ./carData/Chirot.html ./carData/Baumann.html ./carData/Angell.html ./robustbase/SiegelsEx.html ./robustbase/phosphor.html ./robustbase/epilepsy.html ./robustbase/heart.html ./robustbase/toxicity.html ./robustbase/foodstamp.html ./robustbase/salinity.html ./robustbase/cushny.html ./robustbase/ambientNOxCH.html ./robustbase/kootenay.html ./robustbase/pilot.html ./robustbase/alcohol.html ./robustbase/cloud.html ./robustbase/steamUse.html ./robustbase/coleman.html ./robustbase/education.html ./robustbase/condroz.html ./robustbase/pulpfiber.html ./robustbase/wood.html ./robustbase/bushfire.html ./robustbase/delivery.html ./robustbase/los.html ./robustbase/exAM.html ./robustbase/milk.html ./robustbase/pension.html ./robustbase/carrots.html ./robustbase/CrohnD.html ./robustbase/aircraft.html ./robustbase/Animals2.html ./robustbase/biomassTill.html ./robustbase/radarImage.html ./robustbase/wagnerGrowth.html ./robustbase/vaso.html ./robustbase/lactic.html ./robustbase/possumDiv.html ./robustbase/starsCYG.html ./robustbase/telef.html ./robustbase/airmay.html ./robustbase/x30o50.html ./robustbase/NOxEmissions.html ./robustbase/hbk.html ./boot/amis.html ./boot/cav.html ./boot/breslow.html ./boot/urine.html ./boot/cd4.html ./boot/aircondit7.html ./boot/bigcity.html ./boot/aircondit.html ./boot/hirose.html ./boot/fir.html ./boot/remission.html ./boot/tau.html ./boot/salinity.html ./boot/capability.html ./boot/acme.html ./boot/downs.bc.html ./boot/islay.html ./boot/city.html ./boot/beaver.html ./boot/aids.html ./boot/dogs.html ./boot/manaus.html ./boot/channing.html ./boot/wool.html ./boot/co.transfer.html ./boot/nodal.html ./boot/grav.html ./boot/motor.html ./boot/cloth.html ./boot/melanoma.html ./boot/gravity.html ./boot/neuro.html ./boot/paulsen.html ./boot/polar.html ./boot/cane.html ./boot/poisons.html ./boot/tuna.html ./boot/frets.html ./boot/calcium.html ./boot/claridge.html ./boot/coal.html ./boot/ducks.html ./boot/catsM.html ./boot/brambles.html ./boot/aml.html ./boot/darwin.html ./boot/nuclear.html ./boot/nitrofen.html ./boot/survival.html ./datasets/penguins.html ./datasets/presidents.html ./datasets/Harman74.cor.html ./datasets/CO2.html ./datasets/cars.html ./datasets/DNase.html ./datasets/occupationalStatus.html ./datasets/longley.html ./datasets/Harman23.cor.html ./datasets/USJudgeRatings.html ./datasets/nhtemp.html ./datasets/women.html ./datasets/discoveries.html ./datasets/USAccDeaths.html ./datasets/sunspot.year.html ./datasets/Seatbelts.html ./datasets/stackloss.html ./datasets/islands.html ./datasets/BJsales.html ./datasets/VADeaths.html ./datasets/LifeCycleSavings.html ./datasets/OrchardSprays.html ./datasets/esoph.html ./datasets/faithful.html ./datasets/eurodist.html ./datasets/mtcars.html ./datasets/UScitiesD.html ./datasets/morley.html ./datasets/rock.html ./datasets/Loblolly.html ./datasets/nottem.html ./datasets/EuStockMarkets.html ./datasets/BOD.html ./datasets/UKgas.html ./datasets/WorldPhones.html ./datasets/airquality.html ./datasets/infert.html ./datasets/UKDriverDeaths.html ./datasets/austres.html ./datasets/lynx.html ./datasets/USPersonalExpenditure.html ./datasets/swiss.html ./datasets/Titanic.html ./datasets/precip.html ./datasets/sunspots.html ./datasets/lh.html ./datasets/ToothGrowth.html ./datasets/npk.html ./datasets/quakes.html ./datasets/co2.html ./datasets/AirPassengers.html ./datasets/iris.html ./datasets/attitude.html ./datasets/rivers.html ./datasets/USArrests.html ./datasets/Puromycin.html ./datasets/Formaldehyde.html ./datasets/ability.cov.html ./datasets/volcano.html ./datasets/freeny.html ./datasets/Theoph.html ./datasets/ChickWeight.html ./datasets/warpbreaks.html ./datasets/randu.html ./datasets/crimtab.html ./datasets/PlantGrowth.html ./datasets/anscombe.html ./datasets/InsectSprays.html ./datasets/uspop.html ./datasets/attenu.html ./datasets/LakeHuron.html ./datasets/treering.html ./datasets/iris3.html ./datasets/HairEyeColor.html ./datasets/chickwts.html ./datasets/sleep.html ./datasets/euro.html ./datasets/pressure.html ./datasets/Orange.html ./datasets/WWWusage.html ./datasets/UCBAdmissions.html ./datasets/airmiles.html ./datasets/JohnsonJohnson.html ./datasets/gait.html ./datasets/trees.html ./datasets/Indometh.html ./datasets/Nile.html ./datasets/sunspot.month.html ./MASS/survey.html ./MASS/eagles.html ./MASS/Boston.html ./MASS/genotype.html ./MASS/immer.html ./MASS/Insurance.html ./MASS/snails.html ./MASS/rotifer.html ./MASS/Animals.html ./MASS/shoes.html ./MASS/forbes.html ./MASS/deaths.html ./MASS/painters.html ./MASS/birthwt.html ./MASS/beav1.html ./MASS/biopsy.html ./MASS/Cushings.html ./MASS/topo.html ./MASS/OME.html ./MASS/VA.html ./MASS/muscle.html ./MASS/waders.html ./MASS/Melanoma.html ./MASS/Pima.te.html ./MASS/Rubber.html ./MASS/motors.html ./MASS/cpus.html ./MASS/bacteria.html ./MASS/whiteside.html ./MASS/housing.html ./MASS/stormer.html ./MASS/road.html ./MASS/abbey.html ./MASS/npr1.html ./MASS/Sitka.html ./MASS/epil.html ./MASS/galaxies.html ./MASS/npk.html ./MASS/chem.html ./MASS/mcycle.html ./MASS/GAGurine.html ./MASS/gilgais.html ./MASS/hills.html ./MASS/cabbages.html ./MASS/geyser.html ./MASS/minn38.html ./MASS/DDT.html ./MASS/petrol.html ./MASS/Pima.tr2.html ./MASS/fgl.html ./MASS/beav2.html ./MASS/farms.html ./MASS/crabs.html ./MASS/cats.html ./MASS/steam.html ./MASS/coop.html ./MASS/phones.html ./MASS/shuttle.html ./MASS/Rabbit.html ./MASS/SP500.html ./MASS/nlschools.html ./MASS/ships.html ./MASS/caith.html ./MASS/shrimp.html ./MASS/Cars93.html ./MASS/mammals.html ./MASS/leuk.html ./MASS/cement.html ./MASS/drivers.html ./MASS/UScrime.html ./MASS/menarche.html ./MASS/michelson.html ./MASS/oats.html ./MASS/anorexia.html ./MASS/Aids2.html ./MASS/quine.html ./MASS/Traffic.html ./MASS/synth.tr.html ./MASS/Sitka89.html ./MASS/Skye.html ./MASS/newcomb.html ./MASS/wtloss.html ./MASS/accdeaths.html ./MASS/synth.te.html ./MASS/gehan.html ./MASS/UScereal.html ./MASS/Pima.tr.html LC_ALL=C.UTF-8 LANGUAGE=C.UTF-8 python3 tools/export_notebooks_to_python.py Converting robust_models_1 Converting mediation_survival Converting influence_glm_logit Converting discrete_choice_overview Converting statespace_sarimax_faq Converting distributed_estimation Converting regression_diagnostics Converting statespace_arma_0 Converting wls Converting statespace_concentrated_scale Converting tsa_arma_0 Converting statespace_fixed_params Converting plots_boxplots Converting mixed_lm_example Converting statespace_tvpvar_mcmc_cfa Converting statespace_varmax Converting statespace_news Converting postestimation_poisson Converting statespace_dfm_coincident Converting autoregressions Converting treatment_effect Converting lowess Converting chi2_fitting Converting glm_formula Converting ets Converting glm Converting stats_poisson Converting statespace_forecasting Converting autoregressive_distributed_lag Converting interactions_anova Converting statespace_sarimax_pymc3 Converting count_hurdle Converting robust_models_0 Converting gls Converting copula Converting deterministics Converting linear_regression_diagnostics_plots Converting stl_decomposition Converting quasibinomial Converting statespace_custom_models Converting stationarity_detrending_adf_kpss Converting generic_mle Converting statespace_cycles Converting statespace_chandrasekhar Converting contrasts Converting markov_regression Converting categorical_interaction_plot Converting statespace_local_linear_trend Converting tsa_filters Converting variance_components Converting exponential_smoothing Converting statespace_seasonal Converting statespace_structural_harvey_jaeger Converting glm_weights Converting predict Converting tsa_arma_1 Converting mstl_decomposition Converting formulas Converting recursive_ls Converting ols Converting pca_fertility_factors Converting markov_autoregression Converting stats_rankcompare Converting discrete_choice_example Converting gee_score_test_simulation Converting kernel_density Converting statespace_sarimax_internet Converting statespace_sarimax_stata Converting quantile_regression Converting gee_nested_simulation Converting ordinal_regression Converting metaanalysis1 Converting regression_plots Converting tsa_dates Converting theta-model Converting rolling_ls PYTHONPATH=/build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build \ BUILDDIR=/build/reproducible-path/statsmodels-0.14.5+dfsg/build \ STATSMODELS_DATA=/build/reproducible-path/statsmodels-0.14.5+dfsg/build/datacache/ \ LC_ALL=C.UTF-8 LANGUAGE=C.UTF-8 make -C docs html make[2]: Entering directory '/build/reproducible-path/statsmodels-0.14.5+dfsg/docs' Make static directory for images mkdir -p build/html/_static # generate the examples rst files Generating datasets from installed statsmodels.datasets ../tools/dataset_rst.py Writing anes96.rst. Writing cancer.rst. Writing ccard.rst. Writing china_smoking.rst. Writing co2.rst. Writing committee.rst. Writing copper.rst. Writing cpunish.rst. Writing danish_data.rst. Writing elnino.rst. Writing engel.rst. Writing fair.rst. Writing fertility.rst. Writing grunfeld.rst. Writing heart.rst. Writing interest_inflation.rst. Writing longley.rst. Writing macrodata.rst. Writing modechoice.rst. Writing nile.rst. Writing randhie.rst. Writing scotland.rst. Writing spector.rst. Writing stackloss.rst. Writing star98.rst. Writing statecrime.rst. Writing strikes.rst. Writing sunspots.rst. Executing notebooks from examples/notebooks folder mkdir -p build/source/examples/notebooks/generated # Black list notebooks from doc build here ../tools/nbgenerate.py --parallel --report-errors --skip-existing --execute-only --execution-blacklist statespace_custom_models Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/mediation_survival.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/mediation_survival.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/robust_models_1.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/robust_models_1.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/influence_glm_logit.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/influence_glm_logit.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/discrete_choice_overview.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/discrete_choice_overview.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_sarimax_faq.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_sarimax_faq.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/distributed_estimation.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/distributed_estimation.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/regression_diagnostics.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/regression_diagnostics.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_arma_0.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_arma_0.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/wls.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/wls.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_concentrated_scale.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_concentrated_scale.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/tsa_arma_0.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/tsa_arma_0.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_fixed_params.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_fixed_params.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/plots_boxplots.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/plots_boxplots.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/mixed_lm_example.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/mixed_lm_example.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_tvpvar_mcmc_cfa.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_tvpvar_mcmc_cfa.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_varmax.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_varmax.ipynb Traceback (most recent call last): File "/usr/lib/python3.13/runpy.py", line 198, in _run_module_as_main return _run_code(code, main_globals, None, "__main__", mod_spec) File "/usr/lib/python3.13/runpy.py", line 88, in _run_code exec(code, run_globals) ~~~~^^^^^^^^^^^^^^^^^^^ File "/usr/lib/python3/dist-packages/ipykernel_launcher.py", line 18, in app.launch_new_instance() ~~~~~~~~~~~~~~~~~~~~~~~^^ File "/usr/lib/python3/dist-packages/traitlets/config/application.py", line 1074, in launch_instance app.initialize(argv) ~~~~~~~~~~~~~~^^^^^^ File "/usr/lib/python3/dist-packages/traitlets/config/application.py", line 118, in inner return method(app, *args, **kwargs) File "/usr/lib/python3/dist-packages/ipykernel/kernelapp.py", line 692, in initialize self.init_sockets() ~~~~~~~~~~~~~~~~~^^ File "/usr/lib/python3/dist-packages/ipykernel/kernelapp.py", line 346, in init_sockets self.init_iopub(context) ~~~~~~~~~~~~~~~^^^^^^^^^ File "/usr/lib/python3/dist-packages/ipykernel/kernelapp.py", line 375, in init_iopub self.iopub_port = self._bind_socket(self.iopub_socket, self.iopub_port) ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/lib/python3/dist-packages/ipykernel/kernelapp.py", line 253, in _bind_socket return self._try_bind_socket(s, port) ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^ File "/usr/lib/python3/dist-packages/ipykernel/kernelapp.py", line 229, in _try_bind_socket s.bind("tcp://%s:%i" % (self.ip, port)) ~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/usr/lib/python3/dist-packages/zmq/sugar/socket.py", line 320, in bind super().bind(addr) ~~~~~~~~~~~~^^^^^^ File "_zmq.py", line 942, in zmq.backend.cython._zmq.Socket.bind File "_zmq.py", line 180, in zmq.backend.cython._zmq._check_rc zmq.error.ZMQError: Address already in use (addr='tcp://127.0.0.1:40923') Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_news.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_news.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/postestimation_poisson.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/postestimation_poisson.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_dfm_coincident.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_dfm_coincident.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/autoregressions.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/autoregressions.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/treatment_effect.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/treatment_effect.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_fixed_params.ipynb An error occurred while executing the following cell: ------------------ %matplotlib inline from importlib import reload import numpy as np import pandas as pd import statsmodels.api as sm import matplotlib.pyplot as plt from pandas_datareader.data import DataReader ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 9 6 import statsmodels.api as sm 7 import matplotlib.pyplot as plt ----> 9 from pandas_datareader.data import DataReader ModuleNotFoundError: No module named 'pandas_datareader' An error occurred while executing the following cell: ------------------ %matplotlib inline from importlib import reload import numpy as np import pandas as pd import statsmodels.api as sm import matplotlib.pyplot as plt from pandas_datareader.data import DataReader ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 9 6 import statsmodels.api as sm 7 import matplotlib.pyplot as plt ----> 9 from pandas_datareader.data import DataReader ModuleNotFoundError: No module named 'pandas_datareader' ****************************************************************************** Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/lowess.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/lowess.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_varmax.ipynb An error occurred while executing the following cell: ------------------ import requests import shutil def download_file(url): local_filename = url.split('/')[-1] with requests.get(url, stream=True) as r: with open(local_filename, 'wb') as f: shutil.copyfileobj(r.raw, f) return local_filename filename = download_file("https://www.stata-press.com/data/r12/lutkepohl2.dta") dta = pd.read_stata(filename) dta.index = dta.qtr dta.index.freq = dta.index.inferred_freq endog = dta.loc['1960-04-01':'1978-10-01', ['dln_inv', 'dln_inc', 'dln_consump']] ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3/dist-packages/urllib3/connection.py:198, in HTTPConnection._new_conn(self) 197 try: --> 198 sock = connection.create_connection( 199 (self._dns_host, self.port), 200 self.timeout, 201 source_address=self.source_address, 202 socket_options=self.socket_options, 203 ) 204 except socket.gaierror as e: File /usr/lib/python3/dist-packages/urllib3/util/connection.py:85, in create_connection(address, timeout, source_address, socket_options) 84 try: ---> 85 raise err 86 finally: 87 # Break explicitly a reference cycle File /usr/lib/python3/dist-packages/urllib3/util/connection.py:73, in create_connection(address, timeout, source_address, socket_options) 72 sock.bind(source_address) ---> 73 sock.connect(sa) 74 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused The above exception was the direct cause of the following exception: NewConnectionError Traceback (most recent call last) File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:773, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw) 772 try: --> 773 self._prepare_proxy(conn) 774 except (BaseSSLError, OSError, SocketTimeout) as e: File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:1042, in HTTPSConnectionPool._prepare_proxy(self, conn) 1036 conn.set_tunnel( 1037 scheme=tunnel_scheme, 1038 host=self._tunnel_host, 1039 port=self.port, 1040 headers=self.proxy_headers, 1041 ) -> 1042 conn.connect() File /usr/lib/python3/dist-packages/urllib3/connection.py:753, in HTTPSConnection.connect(self) 752 sock: socket.socket | ssl.SSLSocket --> 753 self.sock = sock = self._new_conn() 754 server_hostname: str = self.host File /usr/lib/python3/dist-packages/urllib3/connection.py:213, in HTTPConnection._new_conn(self) 212 except OSError as e: --> 213 raise NewConnectionError( 214 self, f"Failed to establish a new connection: {e}" 215 ) from e 217 sys.audit("http.client.connect", self, self.host, self.port) NewConnectionError: : Failed to establish a new connection: [Errno 111] Connection refused The above exception was the direct cause of the following exception: ProxyError Traceback (most recent call last) ProxyError: ('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused')) The above exception was the direct cause of the following exception: MaxRetryError Traceback (most recent call last) File /usr/lib/python3/dist-packages/requests/adapters.py:644, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies) 643 try: --> 644 resp = conn.urlopen( 645 method=request.method, 646 url=url, 647 body=request.body, 648 headers=request.headers, 649 redirect=False, 650 assert_same_host=False, 651 preload_content=False, 652 decode_content=False, 653 retries=self.max_retries, 654 timeout=timeout, 655 chunked=chunked, 656 ) 658 except (ProtocolError, OSError) as err: File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:841, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw) 839 new_e = ProtocolError("Connection aborted.", new_e) --> 841 retries = retries.increment( 842 method, url, error=new_e, _pool=self, _stacktrace=sys.exc_info()[2] 843 ) 844 retries.sleep() File /usr/lib/python3/dist-packages/urllib3/util/retry.py:519, in Retry.increment(self, method, url, response, error, _pool, _stacktrace) 518 reason = error or ResponseError(cause) --> 519 raise MaxRetryError(_pool, url, reason) from reason # type: ignore[arg-type] 521 log.debug("Incremented Retry for (url='%s'): %r", url, new_retry) MaxRetryError: HTTPSConnectionPool(host='www.stata-press.com', port=443): Max retries exceeded with url: /data/r12/lutkepohl2.dta (Caused by ProxyError('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused'))) During handling of the above exception, another exception occurred: ProxyError Traceback (most recent call last) Cell In[3], line 12 8 shutil.copyfileobj(r.raw, f) 10 return local_filename ---> 12 filename = download_file("https://www.stata-press.com/data/r12/lutkepohl2.dta") 14 dta = pd.read_stata(filename) 15 dta.index = dta.qtr Cell In[3], line 6, in download_file(url) 4 def download_file(url): 5 local_filename = url.split('/')[-1] ----> 6 with requests.get(url, stream=True) as r: 7 with open(local_filename, 'wb') as f: 8 shutil.copyfileobj(r.raw, f) File /usr/lib/python3/dist-packages/requests/api.py:73, in get(url, params, **kwargs) 62 def get(url, params=None, **kwargs): 63 r"""Sends a GET request. 64 65 :param url: URL for the new :class:`Request` object. (...) 70 :rtype: requests.Response 71 """ ---> 73 return request("get", url, params=params, **kwargs) File /usr/lib/python3/dist-packages/requests/api.py:59, in request(method, url, **kwargs) 55 # By using the 'with' statement we are sure the session is closed, thus we 56 # avoid leaving sockets open which can trigger a ResourceWarning in some 57 # cases, and look like a memory leak in others. 58 with sessions.Session() as session: ---> 59 return session.request(method=method, url=url, **kwargs) File /usr/lib/python3/dist-packages/requests/sessions.py:589, in Session.request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json) 584 send_kwargs = { 585 "timeout": timeout, 586 "allow_redirects": allow_redirects, 587 } 588 send_kwargs.update(settings) --> 589 resp = self.send(prep, **send_kwargs) 591 return resp File /usr/lib/python3/dist-packages/requests/sessions.py:703, in Session.send(self, request, **kwargs) 700 start = preferred_clock() 702 # Send the request --> 703 r = adapter.send(request, **kwargs) 705 # Total elapsed time of the request (approximately) 706 elapsed = preferred_clock() - start File /usr/lib/python3/dist-packages/requests/adapters.py:671, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies) 668 raise RetryError(e, request=request) 670 if isinstance(e.reason, _ProxyError): --> 671 raise ProxyError(e, request=request) 673 if isinstance(e.reason, _SSLError): 674 # This branch is for urllib3 v1.22 and later. 675 raise SSLError(e, request=request) ProxyError: HTTPSConnectionPool(host='www.stata-press.com', port=443): Max retries exceeded with url: /data/r12/lutkepohl2.dta (Caused by ProxyError('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused'))) An error occurred while executing the following cell: ------------------ import requests import shutil def download_file(url): local_filename = url.split('/')[-1] with requests.get(url, stream=True) as r: with open(local_filename, 'wb') as f: shutil.copyfileobj(r.raw, f) return local_filename filename = download_file("https://www.stata-press.com/data/r12/lutkepohl2.dta") dta = pd.read_stata(filename) dta.index = dta.qtr dta.index.freq = dta.index.inferred_freq endog = dta.loc['1960-04-01':'1978-10-01', ['dln_inv', 'dln_inc', 'dln_consump']] ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3/dist-packages/urllib3/connection.py:198, in HTTPConnection._new_conn(self) 197 try: --> 198 sock = connection.create_connection( 199 (self._dns_host, self.port), 200 self.timeout, 201 source_address=self.source_address, 202 socket_options=self.socket_options, 203 ) 204 except socket.gaierror as e: File /usr/lib/python3/dist-packages/urllib3/util/connection.py:85, in create_connection(address, timeout, source_address, socket_options) 84 try: ---> 85 raise err 86 finally: 87 # Break explicitly a reference cycle File /usr/lib/python3/dist-packages/urllib3/util/connection.py:73, in create_connection(address, timeout, source_address, socket_options) 72 sock.bind(source_address) ---> 73 sock.connect(sa) 74 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused The above exception was the direct cause of the following exception: NewConnectionError Traceback (most recent call last) File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:773, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw) 772 try: --> 773 self._prepare_proxy(conn) 774 except (BaseSSLError, OSError, SocketTimeout) as e: File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:1042, in HTTPSConnectionPool._prepare_proxy(self, conn) 1036 conn.set_tunnel( 1037 scheme=tunnel_scheme, 1038 host=self._tunnel_host, 1039 port=self.port, 1040 headers=self.proxy_headers, 1041 ) -> 1042 conn.connect() File /usr/lib/python3/dist-packages/urllib3/connection.py:753, in HTTPSConnection.connect(self) 752 sock: socket.socket | ssl.SSLSocket --> 753 self.sock = sock = self._new_conn() 754 server_hostname: str = self.host File /usr/lib/python3/dist-packages/urllib3/connection.py:213, in HTTPConnection._new_conn(self) 212 except OSError as e: --> 213 raise NewConnectionError( 214 self, f"Failed to establish a new connection: {e}" 215 ) from e 217 sys.audit("http.client.connect", self, self.host, self.port) NewConnectionError: : Failed to establish a new connection: [Errno 111] Connection refused The above exception was the direct cause of the following exception: ProxyError Traceback (most recent call last) ProxyError: ('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused')) The above exception was the direct cause of the following exception: MaxRetryError Traceback (most recent call last) File /usr/lib/python3/dist-packages/requests/adapters.py:644, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies) 643 try: --> 644 resp = conn.urlopen( 645 method=request.method, 646 url=url, 647 body=request.body, 648 headers=request.headers, 649 redirect=False, 650 assert_same_host=False, 651 preload_content=False, 652 decode_content=False, 653 retries=self.max_retries, 654 timeout=timeout, 655 chunked=chunked, 656 ) 658 except (ProtocolError, OSError) as err: File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:841, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw) 839 new_e = ProtocolError("Connection aborted.", new_e) --> 841 retries = retries.increment( 842 method, url, error=new_e, _pool=self, _stacktrace=sys.exc_info()[2] 843 ) 844 retries.sleep() File /usr/lib/python3/dist-packages/urllib3/util/retry.py:519, in Retry.increment(self, method, url, response, error, _pool, _stacktrace) 518 reason = error or ResponseError(cause) --> 519 raise MaxRetryError(_pool, url, reason) from reason # type: ignore[arg-type] 521 log.debug("Incremented Retry for (url='%s'): %r", url, new_retry) MaxRetryError: HTTPSConnectionPool(host='www.stata-press.com', port=443): Max retries exceeded with url: /data/r12/lutkepohl2.dta (Caused by ProxyError('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused'))) During handling of the above exception, another exception occurred: ProxyError Traceback (most recent call last) Cell In[3], line 12 8 shutil.copyfileobj(r.raw, f) 10 return local_filename ---> 12 filename = download_file("https://www.stata-press.com/data/r12/lutkepohl2.dta") 14 dta = pd.read_stata(filename) 15 dta.index = dta.qtr Cell In[3], line 6, in download_file(url) 4 def download_file(url): 5 local_filename = url.split('/')[-1] ----> 6 with requests.get(url, stream=True) as r: 7 with open(local_filename, 'wb') as f: 8 shutil.copyfileobj(r.raw, f) File /usr/lib/python3/dist-packages/requests/api.py:73, in get(url, params, **kwargs) 62 def get(url, params=None, **kwargs): 63 r"""Sends a GET request. 64 65 :param url: URL for the new :class:`Request` object. (...) 70 :rtype: requests.Response 71 """ ---> 73 return request("get", url, params=params, **kwargs) File /usr/lib/python3/dist-packages/requests/api.py:59, in request(method, url, **kwargs) 55 # By using the 'with' statement we are sure the session is closed, thus we 56 # avoid leaving sockets open which can trigger a ResourceWarning in some 57 # cases, and look like a memory leak in others. 58 with sessions.Session() as session: ---> 59 return session.request(method=method, url=url, **kwargs) File /usr/lib/python3/dist-packages/requests/sessions.py:589, in Session.request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json) 584 send_kwargs = { 585 "timeout": timeout, 586 "allow_redirects": allow_redirects, 587 } 588 send_kwargs.update(settings) --> 589 resp = self.send(prep, **send_kwargs) 591 return resp File /usr/lib/python3/dist-packages/requests/sessions.py:703, in Session.send(self, request, **kwargs) 700 start = preferred_clock() 702 # Send the request --> 703 r = adapter.send(request, **kwargs) 705 # Total elapsed time of the request (approximately) 706 elapsed = preferred_clock() - start File /usr/lib/python3/dist-packages/requests/adapters.py:671, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies) 668 raise RetryError(e, request=request) 670 if isinstance(e.reason, _ProxyError): --> 671 raise ProxyError(e, request=request) 673 if isinstance(e.reason, _SSLError): 674 # This branch is for urllib3 v1.22 and later. 675 raise SSLError(e, request=request) ProxyError: HTTPSConnectionPool(host='www.stata-press.com', port=443): Max retries exceeded with url: /data/r12/lutkepohl2.dta (Caused by ProxyError('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused'))) ****************************************************************************** Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/chi2_fitting.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/chi2_fitting.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/glm_formula.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/glm_formula.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/ets.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/ets.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/autoregressions.ipynb An error occurred while executing the following cell: ------------------ %matplotlib inline import matplotlib.pyplot as plt import pandas as pd import pandas_datareader as pdr import seaborn as sns from statsmodels.tsa.api import acf, graphics, pacf from statsmodels.tsa.ar_model import AutoReg, ar_select_order ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 4 2 import matplotlib.pyplot as plt 3 import pandas as pd ----> 4 import pandas_datareader as pdr 5 import seaborn as sns 6 from statsmodels.tsa.api import acf, graphics, pacf ModuleNotFoundError: No module named 'pandas_datareader' An error occurred while executing the following cell: ------------------ %matplotlib inline import matplotlib.pyplot as plt import pandas as pd import pandas_datareader as pdr import seaborn as sns from statsmodels.tsa.api import acf, graphics, pacf from statsmodels.tsa.ar_model import AutoReg, ar_select_order ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 4 2 import matplotlib.pyplot as plt 3 import pandas as pd ----> 4 import pandas_datareader as pdr 5 import seaborn as sns 6 from statsmodels.tsa.api import acf, graphics, pacf ModuleNotFoundError: No module named 'pandas_datareader' ****************************************************************************** Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/glm.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/glm.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/stats_poisson.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/stats_poisson.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_forecasting.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_forecasting.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_news.ipynb An error occurred while executing the following cell: ------------------ import pandas_datareader as pdr levels = pdr.get_data_fred( ["PCEPILFE", "CPILFESL"], start="1999", end="2019" ).to_period("M") infl = np.log(levels).diff().iloc[1:] * 1200 infl.columns = ["PCE", "CPI"] # Remove two outliers and de-mean the series infl.loc["2001-09":"2001-10", "PCE"] = np.nan ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[14], line 1 ----> 1 import pandas_datareader as pdr 3 levels = pdr.get_data_fred( 4 ["PCEPILFE", "CPILFESL"], start="1999", end="2019" 5 ).to_period("M") 6 infl = np.log(levels).diff().iloc[1:] * 1200 ModuleNotFoundError: No module named 'pandas_datareader' An error occurred while executing the following cell: ------------------ import pandas_datareader as pdr levels = pdr.get_data_fred( ["PCEPILFE", "CPILFESL"], start="1999", end="2019" ).to_period("M") infl = np.log(levels).diff().iloc[1:] * 1200 infl.columns = ["PCE", "CPI"] # Remove two outliers and de-mean the series infl.loc["2001-09":"2001-10", "PCE"] = np.nan ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[14], line 1 ----> 1 import pandas_datareader as pdr 3 levels = pdr.get_data_fred( 4 ["PCEPILFE", "CPILFESL"], start="1999", end="2019" 5 ).to_period("M") 6 infl = np.log(levels).diff().iloc[1:] * 1200 ModuleNotFoundError: No module named 'pandas_datareader' ****************************************************************************** Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/autoregressive_distributed_lag.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/autoregressive_distributed_lag.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/interactions_anova.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/interactions_anova.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_dfm_coincident.ipynb An error occurred while executing the following cell: ------------------ from pandas_datareader.data import DataReader # Get the datasets from FRED start = '1979-01-01' end = '2014-12-01' indprod = DataReader('IPMAN', 'fred', start=start, end=end) income = DataReader('W875RX1', 'fred', start=start, end=end) sales = DataReader('CMRMTSPL', 'fred', start=start, end=end) emp = DataReader('PAYEMS', 'fred', start=start, end=end) # dta = pd.concat((indprod, income, sales, emp), axis=1) # dta.columns = ['indprod', 'income', 'sales', 'emp'] ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[2], line 1 ----> 1 from pandas_datareader.data import DataReader 3 # Get the datasets from FRED 4 start = '1979-01-01' ModuleNotFoundError: No module named 'pandas_datareader' An error occurred while executing the following cell: ------------------ from pandas_datareader.data import DataReader # Get the datasets from FRED start = '1979-01-01' end = '2014-12-01' indprod = DataReader('IPMAN', 'fred', start=start, end=end) income = DataReader('W875RX1', 'fred', start=start, end=end) sales = DataReader('CMRMTSPL', 'fred', start=start, end=end) emp = DataReader('PAYEMS', 'fred', start=start, end=end) # dta = pd.concat((indprod, income, sales, emp), axis=1) # dta.columns = ['indprod', 'income', 'sales', 'emp'] ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[2], line 1 ----> 1 from pandas_datareader.data import DataReader 3 # Get the datasets from FRED 4 start = '1979-01-01' ModuleNotFoundError: No module named 'pandas_datareader' ****************************************************************************** Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_sarimax_pymc3.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_sarimax_pymc3.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/count_hurdle.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/count_hurdle.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/robust_models_0.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/robust_models_0.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/gls.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/gls.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_sarimax_pymc3.ipynb An error occurred while executing the following cell: ------------------ %matplotlib inline import matplotlib.pyplot as plt import numpy as np import pandas as pd import pymc3 as pm import statsmodels.api as sm import theano import theano.tensor as tt from pandas.plotting import register_matplotlib_converters from pandas_datareader.data import DataReader plt.style.use("seaborn") register_matplotlib_converters() ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 5 3 import numpy as np 4 import pandas as pd ----> 5 import pymc3 as pm 6 import statsmodels.api as sm 7 import theano ModuleNotFoundError: No module named 'pymc3' An error occurred while executing the following cell: ------------------ %matplotlib inline import matplotlib.pyplot as plt import numpy as np import pandas as pd import pymc3 as pm import statsmodels.api as sm import theano import theano.tensor as tt from pandas.plotting import register_matplotlib_converters from pandas_datareader.data import DataReader plt.style.use("seaborn") register_matplotlib_converters() ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 5 3 import numpy as np 4 import pandas as pd ----> 5 import pymc3 as pm 6 import statsmodels.api as sm 7 import theano ModuleNotFoundError: No module named 'pymc3' ****************************************************************************** Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/copula.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/copula.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/deterministics.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/deterministics.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/interactions_anova.ipynb An error occurred while executing the following cell: ------------------ import os import shutil import numpy as np import requests np.set_printoptions(precision=4, suppress=True) import pandas as pd pd.set_option("display.width", 100) import matplotlib.pyplot as plt from statsmodels.formula.api import ols from statsmodels.graphics.api import abline_plot, interaction_plot from statsmodels.stats.anova import anova_lm def download_file(url, mode="t"): local_filename = url.split("/")[-1] if os.path.exists(local_filename): return local_filename with requests.get(url, stream=True) as r: with open(local_filename, f"w{mode}") as f: f.write(r.text) return local_filename url = "https://raw.githubusercontent.com/statsmodels/smdatasets/main/data/anova/salary/salary.table" salary_table = pd.read_csv(download_file(url), sep="\t") E = salary_table.E M = salary_table.M X = salary_table.X S = salary_table.S ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3/dist-packages/urllib3/connection.py:198, in HTTPConnection._new_conn(self) 197 try: --> 198 sock = connection.create_connection( 199 (self._dns_host, self.port), 200 self.timeout, 201 source_address=self.source_address, 202 socket_options=self.socket_options, 203 ) 204 except socket.gaierror as e: File /usr/lib/python3/dist-packages/urllib3/util/connection.py:85, in create_connection(address, timeout, source_address, socket_options) 84 try: ---> 85 raise err 86 finally: 87 # Break explicitly a reference cycle File /usr/lib/python3/dist-packages/urllib3/util/connection.py:73, in create_connection(address, timeout, source_address, socket_options) 72 sock.bind(source_address) ---> 73 sock.connect(sa) 74 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused The above exception was the direct cause of the following exception: NewConnectionError Traceback (most recent call last) File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:773, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw) 772 try: --> 773 self._prepare_proxy(conn) 774 except (BaseSSLError, OSError, SocketTimeout) as e: File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:1042, in HTTPSConnectionPool._prepare_proxy(self, conn) 1036 conn.set_tunnel( 1037 scheme=tunnel_scheme, 1038 host=self._tunnel_host, 1039 port=self.port, 1040 headers=self.proxy_headers, 1041 ) -> 1042 conn.connect() File /usr/lib/python3/dist-packages/urllib3/connection.py:753, in HTTPSConnection.connect(self) 752 sock: socket.socket | ssl.SSLSocket --> 753 self.sock = sock = self._new_conn() 754 server_hostname: str = self.host File /usr/lib/python3/dist-packages/urllib3/connection.py:213, in HTTPConnection._new_conn(self) 212 except OSError as e: --> 213 raise NewConnectionError( 214 self, f"Failed to establish a new connection: {e}" 215 ) from e 217 sys.audit("http.client.connect", self, self.host, self.port) NewConnectionError: : Failed to establish a new connection: [Errno 111] Connection refused The above exception was the direct cause of the following exception: ProxyError Traceback (most recent call last) ProxyError: ('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused')) The above exception was the direct cause of the following exception: MaxRetryError Traceback (most recent call last) File /usr/lib/python3/dist-packages/requests/adapters.py:644, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies) 643 try: --> 644 resp = conn.urlopen( 645 method=request.method, 646 url=url, 647 body=request.body, 648 headers=request.headers, 649 redirect=False, 650 assert_same_host=False, 651 preload_content=False, 652 decode_content=False, 653 retries=self.max_retries, 654 timeout=timeout, 655 chunked=chunked, 656 ) 658 except (ProtocolError, OSError) as err: File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:841, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw) 839 new_e = ProtocolError("Connection aborted.", new_e) --> 841 retries = retries.increment( 842 method, url, error=new_e, _pool=self, _stacktrace=sys.exc_info()[2] 843 ) 844 retries.sleep() File /usr/lib/python3/dist-packages/urllib3/util/retry.py:519, in Retry.increment(self, method, url, response, error, _pool, _stacktrace) 518 reason = error or ResponseError(cause) --> 519 raise MaxRetryError(_pool, url, reason) from reason # type: ignore[arg-type] 521 log.debug("Incremented Retry for (url='%s'): %r", url, new_retry) MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /statsmodels/smdatasets/main/data/anova/salary/salary.table (Caused by ProxyError('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused'))) During handling of the above exception, another exception occurred: ProxyError Traceback (most recent call last) Cell In[2], line 29 25 return local_filename 28 url = "https://raw.githubusercontent.com/statsmodels/smdatasets/main/data/anova/salary/salary.table" ---> 29 salary_table = pd.read_csv(download_file(url), sep="\t") 31 E = salary_table.E 32 M = salary_table.M Cell In[2], line 22, in download_file(url, mode) 20 if os.path.exists(local_filename): 21 return local_filename ---> 22 with requests.get(url, stream=True) as r: 23 with open(local_filename, f"w{mode}") as f: 24 f.write(r.text) File /usr/lib/python3/dist-packages/requests/api.py:73, in get(url, params, **kwargs) 62 def get(url, params=None, **kwargs): 63 r"""Sends a GET request. 64 65 :param url: URL for the new :class:`Request` object. (...) 70 :rtype: requests.Response 71 """ ---> 73 return request("get", url, params=params, **kwargs) File /usr/lib/python3/dist-packages/requests/api.py:59, in request(method, url, **kwargs) 55 # By using the 'with' statement we are sure the session is closed, thus we 56 # avoid leaving sockets open which can trigger a ResourceWarning in some 57 # cases, and look like a memory leak in others. 58 with sessions.Session() as session: ---> 59 return session.request(method=method, url=url, **kwargs) File /usr/lib/python3/dist-packages/requests/sessions.py:589, in Session.request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json) 584 send_kwargs = { 585 "timeout": timeout, 586 "allow_redirects": allow_redirects, 587 } 588 send_kwargs.update(settings) --> 589 resp = self.send(prep, **send_kwargs) 591 return resp File /usr/lib/python3/dist-packages/requests/sessions.py:703, in Session.send(self, request, **kwargs) 700 start = preferred_clock() 702 # Send the request --> 703 r = adapter.send(request, **kwargs) 705 # Total elapsed time of the request (approximately) 706 elapsed = preferred_clock() - start File /usr/lib/python3/dist-packages/requests/adapters.py:671, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies) 668 raise RetryError(e, request=request) 670 if isinstance(e.reason, _ProxyError): --> 671 raise ProxyError(e, request=request) 673 if isinstance(e.reason, _SSLError): 674 # This branch is for urllib3 v1.22 and later. 675 raise SSLError(e, request=request) ProxyError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /statsmodels/smdatasets/main/data/anova/salary/salary.table (Caused by ProxyError('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused'))) An error occurred while executing the following cell: ------------------ import os import shutil import numpy as np import requests np.set_printoptions(precision=4, suppress=True) import pandas as pd pd.set_option("display.width", 100) import matplotlib.pyplot as plt from statsmodels.formula.api import ols from statsmodels.graphics.api import abline_plot, interaction_plot from statsmodels.stats.anova import anova_lm def download_file(url, mode="t"): local_filename = url.split("/")[-1] if os.path.exists(local_filename): return local_filename with requests.get(url, stream=True) as r: with open(local_filename, f"w{mode}") as f: f.write(r.text) return local_filename url = "https://raw.githubusercontent.com/statsmodels/smdatasets/main/data/anova/salary/salary.table" salary_table = pd.read_csv(download_file(url), sep="\t") E = salary_table.E M = salary_table.M X = salary_table.X S = salary_table.S ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3/dist-packages/urllib3/connection.py:198, in HTTPConnection._new_conn(self) 197 try: --> 198 sock = connection.create_connection( 199 (self._dns_host, self.port), 200 self.timeout, 201 source_address=self.source_address, 202 socket_options=self.socket_options, 203 ) 204 except socket.gaierror as e: File /usr/lib/python3/dist-packages/urllib3/util/connection.py:85, in create_connection(address, timeout, source_address, socket_options) 84 try: ---> 85 raise err 86 finally: 87 # Break explicitly a reference cycle File /usr/lib/python3/dist-packages/urllib3/util/connection.py:73, in create_connection(address, timeout, source_address, socket_options) 72 sock.bind(source_address) ---> 73 sock.connect(sa) 74 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused The above exception was the direct cause of the following exception: NewConnectionError Traceback (most recent call last) File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:773, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw) 772 try: --> 773 self._prepare_proxy(conn) 774 except (BaseSSLError, OSError, SocketTimeout) as e: File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:1042, in HTTPSConnectionPool._prepare_proxy(self, conn) 1036 conn.set_tunnel( 1037 scheme=tunnel_scheme, 1038 host=self._tunnel_host, 1039 port=self.port, 1040 headers=self.proxy_headers, 1041 ) -> 1042 conn.connect() File /usr/lib/python3/dist-packages/urllib3/connection.py:753, in HTTPSConnection.connect(self) 752 sock: socket.socket | ssl.SSLSocket --> 753 self.sock = sock = self._new_conn() 754 server_hostname: str = self.host File /usr/lib/python3/dist-packages/urllib3/connection.py:213, in HTTPConnection._new_conn(self) 212 except OSError as e: --> 213 raise NewConnectionError( 214 self, f"Failed to establish a new connection: {e}" 215 ) from e 217 sys.audit("http.client.connect", self, self.host, self.port) NewConnectionError: : Failed to establish a new connection: [Errno 111] Connection refused The above exception was the direct cause of the following exception: ProxyError Traceback (most recent call last) ProxyError: ('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused')) The above exception was the direct cause of the following exception: MaxRetryError Traceback (most recent call last) File /usr/lib/python3/dist-packages/requests/adapters.py:644, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies) 643 try: --> 644 resp = conn.urlopen( 645 method=request.method, 646 url=url, 647 body=request.body, 648 headers=request.headers, 649 redirect=False, 650 assert_same_host=False, 651 preload_content=False, 652 decode_content=False, 653 retries=self.max_retries, 654 timeout=timeout, 655 chunked=chunked, 656 ) 658 except (ProtocolError, OSError) as err: File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:841, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw) 839 new_e = ProtocolError("Connection aborted.", new_e) --> 841 retries = retries.increment( 842 method, url, error=new_e, _pool=self, _stacktrace=sys.exc_info()[2] 843 ) 844 retries.sleep() File /usr/lib/python3/dist-packages/urllib3/util/retry.py:519, in Retry.increment(self, method, url, response, error, _pool, _stacktrace) 518 reason = error or ResponseError(cause) --> 519 raise MaxRetryError(_pool, url, reason) from reason # type: ignore[arg-type] 521 log.debug("Incremented Retry for (url='%s'): %r", url, new_retry) MaxRetryError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /statsmodels/smdatasets/main/data/anova/salary/salary.table (Caused by ProxyError('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused'))) During handling of the above exception, another exception occurred: ProxyError Traceback (most recent call last) Cell In[2], line 29 25 return local_filename 28 url = "https://raw.githubusercontent.com/statsmodels/smdatasets/main/data/anova/salary/salary.table" ---> 29 salary_table = pd.read_csv(download_file(url), sep="\t") 31 E = salary_table.E 32 M = salary_table.M Cell In[2], line 22, in download_file(url, mode) 20 if os.path.exists(local_filename): 21 return local_filename ---> 22 with requests.get(url, stream=True) as r: 23 with open(local_filename, f"w{mode}") as f: 24 f.write(r.text) File /usr/lib/python3/dist-packages/requests/api.py:73, in get(url, params, **kwargs) 62 def get(url, params=None, **kwargs): 63 r"""Sends a GET request. 64 65 :param url: URL for the new :class:`Request` object. (...) 70 :rtype: requests.Response 71 """ ---> 73 return request("get", url, params=params, **kwargs) File /usr/lib/python3/dist-packages/requests/api.py:59, in request(method, url, **kwargs) 55 # By using the 'with' statement we are sure the session is closed, thus we 56 # avoid leaving sockets open which can trigger a ResourceWarning in some 57 # cases, and look like a memory leak in others. 58 with sessions.Session() as session: ---> 59 return session.request(method=method, url=url, **kwargs) File /usr/lib/python3/dist-packages/requests/sessions.py:589, in Session.request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json) 584 send_kwargs = { 585 "timeout": timeout, 586 "allow_redirects": allow_redirects, 587 } 588 send_kwargs.update(settings) --> 589 resp = self.send(prep, **send_kwargs) 591 return resp File /usr/lib/python3/dist-packages/requests/sessions.py:703, in Session.send(self, request, **kwargs) 700 start = preferred_clock() 702 # Send the request --> 703 r = adapter.send(request, **kwargs) 705 # Total elapsed time of the request (approximately) 706 elapsed = preferred_clock() - start File /usr/lib/python3/dist-packages/requests/adapters.py:671, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies) 668 raise RetryError(e, request=request) 670 if isinstance(e.reason, _ProxyError): --> 671 raise ProxyError(e, request=request) 673 if isinstance(e.reason, _SSLError): 674 # This branch is for urllib3 v1.22 and later. 675 raise SSLError(e, request=request) ProxyError: HTTPSConnectionPool(host='raw.githubusercontent.com', port=443): Max retries exceeded with url: /statsmodels/smdatasets/main/data/anova/salary/salary.table (Caused by ProxyError('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused'))) ****************************************************************************** Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/linear_regression_diagnostics_plots.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/linear_regression_diagnostics_plots.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/stl_decomposition.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/stl_decomposition.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/quasibinomial.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/quasibinomial.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/stationarity_detrending_adf_kpss.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/stationarity_detrending_adf_kpss.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/generic_mle.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/generic_mle.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_cycles.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_cycles.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_chandrasekhar.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_chandrasekhar.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/robust_models_1.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/contrasts.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/contrasts.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/markov_regression.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/markov_regression.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/categorical_interaction_plot.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/categorical_interaction_plot.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/mediation_survival.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/influence_glm_logit.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/discrete_choice_overview.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_local_linear_trend.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_local_linear_trend.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/linear_regression_diagnostics_plots.ipynb An error occurred while executing the following cell: ------------------ # Load data data_url = "https://raw.githubusercontent.com/nguyen-toan/ISLR/07fd968ea484b5f6febc7b392a28eb64329a4945/dataset/Advertising.csv" df = pd.read_csv(data_url).drop('Unnamed: 0', axis=1) df.head() ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3.13/urllib/request.py:1319, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1318 try: -> 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error File /usr/lib/python3.13/http/client.py:1338, in HTTPConnection.request(self, method, url, body, headers, encode_chunked) 1337 """Send a complete request to the server.""" -> 1338 self._send_request(method, url, body, headers, encode_chunked) File /usr/lib/python3.13/http/client.py:1384, in HTTPConnection._send_request(self, method, url, body, headers, encode_chunked) 1383 body = _encode(body, 'body') -> 1384 self.endheaders(body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1333, in HTTPConnection.endheaders(self, message_body, encode_chunked) 1332 raise CannotSendHeader() -> 1333 self._send_output(message_body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1093, in HTTPConnection._send_output(self, message_body, encode_chunked) 1092 del self._buffer[:] -> 1093 self.send(msg) 1095 if message_body is not None: 1096 1097 # create a consistent interface to message_body File /usr/lib/python3.13/http/client.py:1037, in HTTPConnection.send(self, data) 1036 if self.auto_open: -> 1037 self.connect() 1038 else: File /usr/lib/python3.13/http/client.py:1472, in HTTPSConnection.connect(self) 1470 "Connect to a host on a given (SSL) port." -> 1472 super().connect() 1474 if self._tunnel_host: File /usr/lib/python3.13/http/client.py:1003, in HTTPConnection.connect(self) 1002 sys.audit("http.client.connect", self, self.host, self.port) -> 1003 self.sock = self._create_connection( 1004 (self.host,self.port), self.timeout, self.source_address) 1005 # Might fail in OSs that don't implement TCP_NODELAY File /usr/lib/python3.13/socket.py:864, in create_connection(address, timeout, source_address, all_errors) 863 if not all_errors: --> 864 raise exceptions[0] 865 raise ExceptionGroup("create_connection failed", exceptions) File /usr/lib/python3.13/socket.py:849, in create_connection(address, timeout, source_address, all_errors) 848 sock.bind(source_address) --> 849 sock.connect(sa) 850 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused During handling of the above exception, another exception occurred: URLError Traceback (most recent call last) Cell In[2], line 3 1 # Load data 2 data_url = "https://raw.githubusercontent.com/nguyen-toan/ISLR/07fd968ea484b5f6febc7b392a28eb64329a4945/dataset/Advertising.csv" ----> 3 df = pd.read_csv(data_url).drop('Unnamed: 0', axis=1) 4 df.head() File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1026, in read_csv(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend) 1013 kwds_defaults = _refine_defaults_read( 1014 dialect, 1015 delimiter, (...) 1022 dtype_backend=dtype_backend, 1023 ) 1024 kwds.update(kwds_defaults) -> 1026 return _read(filepath_or_buffer, kwds) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:620, in _read(filepath_or_buffer, kwds) 617 _validate_names(kwds.get("names", None)) 619 # Create the parser. --> 620 parser = TextFileReader(filepath_or_buffer, **kwds) 622 if chunksize or iterator: 623 return parser File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1620, in TextFileReader.__init__(self, f, engine, **kwds) 1617 self.options["has_index_names"] = kwds["has_index_names"] 1619 self.handles: IOHandles | None = None -> 1620 self._engine = self._make_engine(f, self.engine) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1880, in TextFileReader._make_engine(self, f, engine) 1878 if "b" not in mode: 1879 mode += "b" -> 1880 self.handles = get_handle( 1881 f, 1882 mode, 1883 encoding=self.options.get("encoding", None), 1884 compression=self.options.get("compression", None), 1885 memory_map=self.options.get("memory_map", False), 1886 is_text=is_text, 1887 errors=self.options.get("encoding_errors", "strict"), 1888 storage_options=self.options.get("storage_options", None), 1889 ) 1890 assert self.handles is not None 1891 f = self.handles.handle File /usr/lib/python3/dist-packages/pandas/io/common.py:728, in get_handle(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options) 725 codecs.lookup_error(errors) 727 # open URLs --> 728 ioargs = _get_filepath_or_buffer( 729 path_or_buf, 730 encoding=encoding, 731 compression=compression, 732 mode=mode, 733 storage_options=storage_options, 734 ) 736 handle = ioargs.filepath_or_buffer 737 handles: list[BaseBuffer] File /usr/lib/python3/dist-packages/pandas/io/common.py:384, in _get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode, storage_options) 382 # assuming storage_options is to be interpreted as headers 383 req_info = urllib.request.Request(filepath_or_buffer, headers=storage_options) --> 384 with urlopen(req_info) as req: 385 content_encoding = req.headers.get("Content-Encoding", None) 386 if content_encoding == "gzip": 387 # Override compression based on Content-Encoding header File /usr/lib/python3/dist-packages/pandas/io/common.py:289, in urlopen(*args, **kwargs) 283 """ 284 Lazy-import wrapper for stdlib urlopen, as that imports a big chunk of 285 the stdlib. 286 """ 287 import urllib.request --> 289 return urllib.request.urlopen(*args, **kwargs) File /usr/lib/python3.13/urllib/request.py:189, in urlopen(url, data, timeout, context) 187 else: 188 opener = _opener --> 189 return opener.open(url, data, timeout) File /usr/lib/python3.13/urllib/request.py:489, in OpenerDirector.open(self, fullurl, data, timeout) 486 req = meth(req) 488 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method()) --> 489 response = self._open(req, data) 491 # post-process response 492 meth_name = protocol+"_response" File /usr/lib/python3.13/urllib/request.py:506, in OpenerDirector._open(self, req, data) 503 return result 505 protocol = req.type --> 506 result = self._call_chain(self.handle_open, protocol, protocol + 507 '_open', req) 508 if result: 509 return result File /usr/lib/python3.13/urllib/request.py:466, in OpenerDirector._call_chain(self, chain, kind, meth_name, *args) 464 for handler in handlers: 465 func = getattr(handler, meth_name) --> 466 result = func(*args) 467 if result is not None: 468 return result File /usr/lib/python3.13/urllib/request.py:1367, in HTTPSHandler.https_open(self, req) 1366 def https_open(self, req): -> 1367 return self.do_open(http.client.HTTPSConnection, req, 1368 context=self._context) File /usr/lib/python3.13/urllib/request.py:1322, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error -> 1322 raise URLError(err) 1323 r = h.getresponse() 1324 except: URLError: An error occurred while executing the following cell: ------------------ # Load data data_url = "https://raw.githubusercontent.com/nguyen-toan/ISLR/07fd968ea484b5f6febc7b392a28eb64329a4945/dataset/Advertising.csv" df = pd.read_csv(data_url).drop('Unnamed: 0', axis=1) df.head() ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3.13/urllib/request.py:1319, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1318 try: -> 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error File /usr/lib/python3.13/http/client.py:1338, in HTTPConnection.request(self, method, url, body, headers, encode_chunked) 1337 """Send a complete request to the server.""" -> 1338 self._send_request(method, url, body, headers, encode_chunked) File /usr/lib/python3.13/http/client.py:1384, in HTTPConnection._send_request(self, method, url, body, headers, encode_chunked) 1383 body = _encode(body, 'body') -> 1384 self.endheaders(body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1333, in HTTPConnection.endheaders(self, message_body, encode_chunked) 1332 raise CannotSendHeader() -> 1333 self._send_output(message_body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1093, in HTTPConnection._send_output(self, message_body, encode_chunked) 1092 del self._buffer[:] -> 1093 self.send(msg) 1095 if message_body is not None: 1096 1097 # create a consistent interface to message_body File /usr/lib/python3.13/http/client.py:1037, in HTTPConnection.send(self, data) 1036 if self.auto_open: -> 1037 self.connect() 1038 else: File /usr/lib/python3.13/http/client.py:1472, in HTTPSConnection.connect(self) 1470 "Connect to a host on a given (SSL) port." -> 1472 super().connect() 1474 if self._tunnel_host: File /usr/lib/python3.13/http/client.py:1003, in HTTPConnection.connect(self) 1002 sys.audit("http.client.connect", self, self.host, self.port) -> 1003 self.sock = self._create_connection( 1004 (self.host,self.port), self.timeout, self.source_address) 1005 # Might fail in OSs that don't implement TCP_NODELAY File /usr/lib/python3.13/socket.py:864, in create_connection(address, timeout, source_address, all_errors) 863 if not all_errors: --> 864 raise exceptions[0] 865 raise ExceptionGroup("create_connection failed", exceptions) File /usr/lib/python3.13/socket.py:849, in create_connection(address, timeout, source_address, all_errors) 848 sock.bind(source_address) --> 849 sock.connect(sa) 850 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused During handling of the above exception, another exception occurred: URLError Traceback (most recent call last) Cell In[2], line 3 1 # Load data 2 data_url = "https://raw.githubusercontent.com/nguyen-toan/ISLR/07fd968ea484b5f6febc7b392a28eb64329a4945/dataset/Advertising.csv" ----> 3 df = pd.read_csv(data_url).drop('Unnamed: 0', axis=1) 4 df.head() File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1026, in read_csv(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend) 1013 kwds_defaults = _refine_defaults_read( 1014 dialect, 1015 delimiter, (...) 1022 dtype_backend=dtype_backend, 1023 ) 1024 kwds.update(kwds_defaults) -> 1026 return _read(filepath_or_buffer, kwds) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:620, in _read(filepath_or_buffer, kwds) 617 _validate_names(kwds.get("names", None)) 619 # Create the parser. --> 620 parser = TextFileReader(filepath_or_buffer, **kwds) 622 if chunksize or iterator: 623 return parser File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1620, in TextFileReader.__init__(self, f, engine, **kwds) 1617 self.options["has_index_names"] = kwds["has_index_names"] 1619 self.handles: IOHandles | None = None -> 1620 self._engine = self._make_engine(f, self.engine) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1880, in TextFileReader._make_engine(self, f, engine) 1878 if "b" not in mode: 1879 mode += "b" -> 1880 self.handles = get_handle( 1881 f, 1882 mode, 1883 encoding=self.options.get("encoding", None), 1884 compression=self.options.get("compression", None), 1885 memory_map=self.options.get("memory_map", False), 1886 is_text=is_text, 1887 errors=self.options.get("encoding_errors", "strict"), 1888 storage_options=self.options.get("storage_options", None), 1889 ) 1890 assert self.handles is not None 1891 f = self.handles.handle File /usr/lib/python3/dist-packages/pandas/io/common.py:728, in get_handle(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options) 725 codecs.lookup_error(errors) 727 # open URLs --> 728 ioargs = _get_filepath_or_buffer( 729 path_or_buf, 730 encoding=encoding, 731 compression=compression, 732 mode=mode, 733 storage_options=storage_options, 734 ) 736 handle = ioargs.filepath_or_buffer 737 handles: list[BaseBuffer] File /usr/lib/python3/dist-packages/pandas/io/common.py:384, in _get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode, storage_options) 382 # assuming storage_options is to be interpreted as headers 383 req_info = urllib.request.Request(filepath_or_buffer, headers=storage_options) --> 384 with urlopen(req_info) as req: 385 content_encoding = req.headers.get("Content-Encoding", None) 386 if content_encoding == "gzip": 387 # Override compression based on Content-Encoding header File /usr/lib/python3/dist-packages/pandas/io/common.py:289, in urlopen(*args, **kwargs) 283 """ 284 Lazy-import wrapper for stdlib urlopen, as that imports a big chunk of 285 the stdlib. 286 """ 287 import urllib.request --> 289 return urllib.request.urlopen(*args, **kwargs) File /usr/lib/python3.13/urllib/request.py:189, in urlopen(url, data, timeout, context) 187 else: 188 opener = _opener --> 189 return opener.open(url, data, timeout) File /usr/lib/python3.13/urllib/request.py:489, in OpenerDirector.open(self, fullurl, data, timeout) 486 req = meth(req) 488 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method()) --> 489 response = self._open(req, data) 491 # post-process response 492 meth_name = protocol+"_response" File /usr/lib/python3.13/urllib/request.py:506, in OpenerDirector._open(self, req, data) 503 return result 505 protocol = req.type --> 506 result = self._call_chain(self.handle_open, protocol, protocol + 507 '_open', req) 508 if result: 509 return result File /usr/lib/python3.13/urllib/request.py:466, in OpenerDirector._call_chain(self, chain, kind, meth_name, *args) 464 for handler in handlers: 465 func = getattr(handler, meth_name) --> 466 result = func(*args) 467 if result is not None: 468 return result File /usr/lib/python3.13/urllib/request.py:1367, in HTTPSHandler.https_open(self, req) 1366 def https_open(self, req): -> 1367 return self.do_open(http.client.HTTPSConnection, req, 1368 context=self._context) File /usr/lib/python3.13/urllib/request.py:1322, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error -> 1322 raise URLError(err) 1323 r = h.getresponse() 1324 except: URLError: ****************************************************************************** Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/tsa_filters.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/tsa_filters.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/variance_components.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/variance_components.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/exponential_smoothing.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/exponential_smoothing.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_cycles.ipynb An error occurred while executing the following cell: ------------------ from pandas_datareader.data import DataReader endog = DataReader('UNRATE', 'fred', start='1954-01-01') endog.index.freq = endog.index.inferred_freq ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[3], line 1 ----> 1 from pandas_datareader.data import DataReader 2 endog = DataReader('UNRATE', 'fred', start='1954-01-01') 3 endog.index.freq = endog.index.inferred_freq ModuleNotFoundError: No module named 'pandas_datareader' An error occurred while executing the following cell: ------------------ from pandas_datareader.data import DataReader endog = DataReader('UNRATE', 'fred', start='1954-01-01') endog.index.freq = endog.index.inferred_freq ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[3], line 1 ----> 1 from pandas_datareader.data import DataReader 2 endog = DataReader('UNRATE', 'fred', start='1954-01-01') 3 endog.index.freq = endog.index.inferred_freq ModuleNotFoundError: No module named 'pandas_datareader' ****************************************************************************** Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_seasonal.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_seasonal.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_structural_harvey_jaeger.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_structural_harvey_jaeger.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_chandrasekhar.ipynb An error occurred while executing the following cell: ------------------ %matplotlib inline import numpy as np import pandas as pd import statsmodels.api as sm import matplotlib.pyplot as plt from pandas_datareader.data import DataReader ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 8 5 import statsmodels.api as sm 6 import matplotlib.pyplot as plt ----> 8 from pandas_datareader.data import DataReader ModuleNotFoundError: No module named 'pandas_datareader' An error occurred while executing the following cell: ------------------ %matplotlib inline import numpy as np import pandas as pd import statsmodels.api as sm import matplotlib.pyplot as plt from pandas_datareader.data import DataReader ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 8 5 import statsmodels.api as sm 6 import matplotlib.pyplot as plt ----> 8 from pandas_datareader.data import DataReader ModuleNotFoundError: No module named 'pandas_datareader' ****************************************************************************** Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/glm_weights.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/glm_weights.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/predict.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/predict.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/autoregressive_distributed_lag.ipynb An error occurred while executing the following cell: ------------------ greene = pd.read_fwf("http://www.stern.nyu.edu/~wgreene/Text/Edition7/TableF5-2.txt") greene.head() ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3.13/urllib/request.py:1319, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1318 try: -> 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error File /usr/lib/python3.13/http/client.py:1338, in HTTPConnection.request(self, method, url, body, headers, encode_chunked) 1337 """Send a complete request to the server.""" -> 1338 self._send_request(method, url, body, headers, encode_chunked) File /usr/lib/python3.13/http/client.py:1384, in HTTPConnection._send_request(self, method, url, body, headers, encode_chunked) 1383 body = _encode(body, 'body') -> 1384 self.endheaders(body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1333, in HTTPConnection.endheaders(self, message_body, encode_chunked) 1332 raise CannotSendHeader() -> 1333 self._send_output(message_body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1093, in HTTPConnection._send_output(self, message_body, encode_chunked) 1092 del self._buffer[:] -> 1093 self.send(msg) 1095 if message_body is not None: 1096 1097 # create a consistent interface to message_body File /usr/lib/python3.13/http/client.py:1037, in HTTPConnection.send(self, data) 1036 if self.auto_open: -> 1037 self.connect() 1038 else: File /usr/lib/python3.13/http/client.py:1003, in HTTPConnection.connect(self) 1002 sys.audit("http.client.connect", self, self.host, self.port) -> 1003 self.sock = self._create_connection( 1004 (self.host,self.port), self.timeout, self.source_address) 1005 # Might fail in OSs that don't implement TCP_NODELAY File /usr/lib/python3.13/socket.py:864, in create_connection(address, timeout, source_address, all_errors) 863 if not all_errors: --> 864 raise exceptions[0] 865 raise ExceptionGroup("create_connection failed", exceptions) File /usr/lib/python3.13/socket.py:849, in create_connection(address, timeout, source_address, all_errors) 848 sock.bind(source_address) --> 849 sock.connect(sa) 850 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused During handling of the above exception, another exception occurred: URLError Traceback (most recent call last) Cell In[19], line 1 ----> 1 greene = pd.read_fwf("http://www.stern.nyu.edu/~wgreene/Text/Edition7/TableF5-2.txt") 2 greene.head() File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1565, in read_fwf(filepath_or_buffer, colspecs, widths, infer_nrows, dtype_backend, iterator, chunksize, **kwds) 1563 check_dtype_backend(dtype_backend) 1564 kwds["dtype_backend"] = dtype_backend -> 1565 return _read(filepath_or_buffer, kwds) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:620, in _read(filepath_or_buffer, kwds) 617 _validate_names(kwds.get("names", None)) 619 # Create the parser. --> 620 parser = TextFileReader(filepath_or_buffer, **kwds) 622 if chunksize or iterator: 623 return parser File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1620, in TextFileReader.__init__(self, f, engine, **kwds) 1617 self.options["has_index_names"] = kwds["has_index_names"] 1619 self.handles: IOHandles | None = None -> 1620 self._engine = self._make_engine(f, self.engine) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1880, in TextFileReader._make_engine(self, f, engine) 1878 if "b" not in mode: 1879 mode += "b" -> 1880 self.handles = get_handle( 1881 f, 1882 mode, 1883 encoding=self.options.get("encoding", None), 1884 compression=self.options.get("compression", None), 1885 memory_map=self.options.get("memory_map", False), 1886 is_text=is_text, 1887 errors=self.options.get("encoding_errors", "strict"), 1888 storage_options=self.options.get("storage_options", None), 1889 ) 1890 assert self.handles is not None 1891 f = self.handles.handle File /usr/lib/python3/dist-packages/pandas/io/common.py:728, in get_handle(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options) 725 codecs.lookup_error(errors) 727 # open URLs --> 728 ioargs = _get_filepath_or_buffer( 729 path_or_buf, 730 encoding=encoding, 731 compression=compression, 732 mode=mode, 733 storage_options=storage_options, 734 ) 736 handle = ioargs.filepath_or_buffer 737 handles: list[BaseBuffer] File /usr/lib/python3/dist-packages/pandas/io/common.py:384, in _get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode, storage_options) 382 # assuming storage_options is to be interpreted as headers 383 req_info = urllib.request.Request(filepath_or_buffer, headers=storage_options) --> 384 with urlopen(req_info) as req: 385 content_encoding = req.headers.get("Content-Encoding", None) 386 if content_encoding == "gzip": 387 # Override compression based on Content-Encoding header File /usr/lib/python3/dist-packages/pandas/io/common.py:289, in urlopen(*args, **kwargs) 283 """ 284 Lazy-import wrapper for stdlib urlopen, as that imports a big chunk of 285 the stdlib. 286 """ 287 import urllib.request --> 289 return urllib.request.urlopen(*args, **kwargs) File /usr/lib/python3.13/urllib/request.py:189, in urlopen(url, data, timeout, context) 187 else: 188 opener = _opener --> 189 return opener.open(url, data, timeout) File /usr/lib/python3.13/urllib/request.py:489, in OpenerDirector.open(self, fullurl, data, timeout) 486 req = meth(req) 488 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method()) --> 489 response = self._open(req, data) 491 # post-process response 492 meth_name = protocol+"_response" File /usr/lib/python3.13/urllib/request.py:506, in OpenerDirector._open(self, req, data) 503 return result 505 protocol = req.type --> 506 result = self._call_chain(self.handle_open, protocol, protocol + 507 '_open', req) 508 if result: 509 return result File /usr/lib/python3.13/urllib/request.py:466, in OpenerDirector._call_chain(self, chain, kind, meth_name, *args) 464 for handler in handlers: 465 func = getattr(handler, meth_name) --> 466 result = func(*args) 467 if result is not None: 468 return result File /usr/lib/python3.13/urllib/request.py:1348, in HTTPHandler.http_open(self, req) 1347 def http_open(self, req): -> 1348 return self.do_open(http.client.HTTPConnection, req) File /usr/lib/python3.13/urllib/request.py:1322, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error -> 1322 raise URLError(err) 1323 r = h.getresponse() 1324 except: URLError: An error occurred while executing the following cell: ------------------ greene = pd.read_fwf("http://www.stern.nyu.edu/~wgreene/Text/Edition7/TableF5-2.txt") greene.head() ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3.13/urllib/request.py:1319, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1318 try: -> 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error File /usr/lib/python3.13/http/client.py:1338, in HTTPConnection.request(self, method, url, body, headers, encode_chunked) 1337 """Send a complete request to the server.""" -> 1338 self._send_request(method, url, body, headers, encode_chunked) File /usr/lib/python3.13/http/client.py:1384, in HTTPConnection._send_request(self, method, url, body, headers, encode_chunked) 1383 body = _encode(body, 'body') -> 1384 self.endheaders(body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1333, in HTTPConnection.endheaders(self, message_body, encode_chunked) 1332 raise CannotSendHeader() -> 1333 self._send_output(message_body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1093, in HTTPConnection._send_output(self, message_body, encode_chunked) 1092 del self._buffer[:] -> 1093 self.send(msg) 1095 if message_body is not None: 1096 1097 # create a consistent interface to message_body File /usr/lib/python3.13/http/client.py:1037, in HTTPConnection.send(self, data) 1036 if self.auto_open: -> 1037 self.connect() 1038 else: File /usr/lib/python3.13/http/client.py:1003, in HTTPConnection.connect(self) 1002 sys.audit("http.client.connect", self, self.host, self.port) -> 1003 self.sock = self._create_connection( 1004 (self.host,self.port), self.timeout, self.source_address) 1005 # Might fail in OSs that don't implement TCP_NODELAY File /usr/lib/python3.13/socket.py:864, in create_connection(address, timeout, source_address, all_errors) 863 if not all_errors: --> 864 raise exceptions[0] 865 raise ExceptionGroup("create_connection failed", exceptions) File /usr/lib/python3.13/socket.py:849, in create_connection(address, timeout, source_address, all_errors) 848 sock.bind(source_address) --> 849 sock.connect(sa) 850 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused During handling of the above exception, another exception occurred: URLError Traceback (most recent call last) Cell In[19], line 1 ----> 1 greene = pd.read_fwf("http://www.stern.nyu.edu/~wgreene/Text/Edition7/TableF5-2.txt") 2 greene.head() File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1565, in read_fwf(filepath_or_buffer, colspecs, widths, infer_nrows, dtype_backend, iterator, chunksize, **kwds) 1563 check_dtype_backend(dtype_backend) 1564 kwds["dtype_backend"] = dtype_backend -> 1565 return _read(filepath_or_buffer, kwds) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:620, in _read(filepath_or_buffer, kwds) 617 _validate_names(kwds.get("names", None)) 619 # Create the parser. --> 620 parser = TextFileReader(filepath_or_buffer, **kwds) 622 if chunksize or iterator: 623 return parser File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1620, in TextFileReader.__init__(self, f, engine, **kwds) 1617 self.options["has_index_names"] = kwds["has_index_names"] 1619 self.handles: IOHandles | None = None -> 1620 self._engine = self._make_engine(f, self.engine) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1880, in TextFileReader._make_engine(self, f, engine) 1878 if "b" not in mode: 1879 mode += "b" -> 1880 self.handles = get_handle( 1881 f, 1882 mode, 1883 encoding=self.options.get("encoding", None), 1884 compression=self.options.get("compression", None), 1885 memory_map=self.options.get("memory_map", False), 1886 is_text=is_text, 1887 errors=self.options.get("encoding_errors", "strict"), 1888 storage_options=self.options.get("storage_options", None), 1889 ) 1890 assert self.handles is not None 1891 f = self.handles.handle File /usr/lib/python3/dist-packages/pandas/io/common.py:728, in get_handle(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options) 725 codecs.lookup_error(errors) 727 # open URLs --> 728 ioargs = _get_filepath_or_buffer( 729 path_or_buf, 730 encoding=encoding, 731 compression=compression, 732 mode=mode, 733 storage_options=storage_options, 734 ) 736 handle = ioargs.filepath_or_buffer 737 handles: list[BaseBuffer] File /usr/lib/python3/dist-packages/pandas/io/common.py:384, in _get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode, storage_options) 382 # assuming storage_options is to be interpreted as headers 383 req_info = urllib.request.Request(filepath_or_buffer, headers=storage_options) --> 384 with urlopen(req_info) as req: 385 content_encoding = req.headers.get("Content-Encoding", None) 386 if content_encoding == "gzip": 387 # Override compression based on Content-Encoding header File /usr/lib/python3/dist-packages/pandas/io/common.py:289, in urlopen(*args, **kwargs) 283 """ 284 Lazy-import wrapper for stdlib urlopen, as that imports a big chunk of 285 the stdlib. 286 """ 287 import urllib.request --> 289 return urllib.request.urlopen(*args, **kwargs) File /usr/lib/python3.13/urllib/request.py:189, in urlopen(url, data, timeout, context) 187 else: 188 opener = _opener --> 189 return opener.open(url, data, timeout) File /usr/lib/python3.13/urllib/request.py:489, in OpenerDirector.open(self, fullurl, data, timeout) 486 req = meth(req) 488 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method()) --> 489 response = self._open(req, data) 491 # post-process response 492 meth_name = protocol+"_response" File /usr/lib/python3.13/urllib/request.py:506, in OpenerDirector._open(self, req, data) 503 return result 505 protocol = req.type --> 506 result = self._call_chain(self.handle_open, protocol, protocol + 507 '_open', req) 508 if result: 509 return result File /usr/lib/python3.13/urllib/request.py:466, in OpenerDirector._call_chain(self, chain, kind, meth_name, *args) 464 for handler in handlers: 465 func = getattr(handler, meth_name) --> 466 result = func(*args) 467 if result is not None: 468 return result File /usr/lib/python3.13/urllib/request.py:1348, in HTTPHandler.http_open(self, req) 1347 def http_open(self, req): -> 1348 return self.do_open(http.client.HTTPConnection, req) File /usr/lib/python3.13/urllib/request.py:1322, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error -> 1322 raise URLError(err) 1323 r = h.getresponse() 1324 except: URLError: ****************************************************************************** Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/tsa_arma_1.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/tsa_arma_1.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/contrasts.ipynb An error occurred while executing the following cell: ------------------ import pandas as pd url = "https://stats.idre.ucla.edu/stat/data/hsb2.csv" hsb2 = pd.read_table(url, delimiter=",") ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3.13/urllib/request.py:1319, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1318 try: -> 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error File /usr/lib/python3.13/http/client.py:1338, in HTTPConnection.request(self, method, url, body, headers, encode_chunked) 1337 """Send a complete request to the server.""" -> 1338 self._send_request(method, url, body, headers, encode_chunked) File /usr/lib/python3.13/http/client.py:1384, in HTTPConnection._send_request(self, method, url, body, headers, encode_chunked) 1383 body = _encode(body, 'body') -> 1384 self.endheaders(body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1333, in HTTPConnection.endheaders(self, message_body, encode_chunked) 1332 raise CannotSendHeader() -> 1333 self._send_output(message_body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1093, in HTTPConnection._send_output(self, message_body, encode_chunked) 1092 del self._buffer[:] -> 1093 self.send(msg) 1095 if message_body is not None: 1096 1097 # create a consistent interface to message_body File /usr/lib/python3.13/http/client.py:1037, in HTTPConnection.send(self, data) 1036 if self.auto_open: -> 1037 self.connect() 1038 else: File /usr/lib/python3.13/http/client.py:1472, in HTTPSConnection.connect(self) 1470 "Connect to a host on a given (SSL) port." -> 1472 super().connect() 1474 if self._tunnel_host: File /usr/lib/python3.13/http/client.py:1003, in HTTPConnection.connect(self) 1002 sys.audit("http.client.connect", self, self.host, self.port) -> 1003 self.sock = self._create_connection( 1004 (self.host,self.port), self.timeout, self.source_address) 1005 # Might fail in OSs that don't implement TCP_NODELAY File /usr/lib/python3.13/socket.py:864, in create_connection(address, timeout, source_address, all_errors) 863 if not all_errors: --> 864 raise exceptions[0] 865 raise ExceptionGroup("create_connection failed", exceptions) File /usr/lib/python3.13/socket.py:849, in create_connection(address, timeout, source_address, all_errors) 848 sock.bind(source_address) --> 849 sock.connect(sa) 850 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused During handling of the above exception, another exception occurred: URLError Traceback (most recent call last) Cell In[2], line 4 1 import pandas as pd 3 url = "https://stats.idre.ucla.edu/stat/data/hsb2.csv" ----> 4 hsb2 = pd.read_table(url, delimiter=",") File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1405, in read_table(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend) 1392 kwds_defaults = _refine_defaults_read( 1393 dialect, 1394 delimiter, (...) 1401 dtype_backend=dtype_backend, 1402 ) 1403 kwds.update(kwds_defaults) -> 1405 return _read(filepath_or_buffer, kwds) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:620, in _read(filepath_or_buffer, kwds) 617 _validate_names(kwds.get("names", None)) 619 # Create the parser. --> 620 parser = TextFileReader(filepath_or_buffer, **kwds) 622 if chunksize or iterator: 623 return parser File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1620, in TextFileReader.__init__(self, f, engine, **kwds) 1617 self.options["has_index_names"] = kwds["has_index_names"] 1619 self.handles: IOHandles | None = None -> 1620 self._engine = self._make_engine(f, self.engine) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1880, in TextFileReader._make_engine(self, f, engine) 1878 if "b" not in mode: 1879 mode += "b" -> 1880 self.handles = get_handle( 1881 f, 1882 mode, 1883 encoding=self.options.get("encoding", None), 1884 compression=self.options.get("compression", None), 1885 memory_map=self.options.get("memory_map", False), 1886 is_text=is_text, 1887 errors=self.options.get("encoding_errors", "strict"), 1888 storage_options=self.options.get("storage_options", None), 1889 ) 1890 assert self.handles is not None 1891 f = self.handles.handle File /usr/lib/python3/dist-packages/pandas/io/common.py:728, in get_handle(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options) 725 codecs.lookup_error(errors) 727 # open URLs --> 728 ioargs = _get_filepath_or_buffer( 729 path_or_buf, 730 encoding=encoding, 731 compression=compression, 732 mode=mode, 733 storage_options=storage_options, 734 ) 736 handle = ioargs.filepath_or_buffer 737 handles: list[BaseBuffer] File /usr/lib/python3/dist-packages/pandas/io/common.py:384, in _get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode, storage_options) 382 # assuming storage_options is to be interpreted as headers 383 req_info = urllib.request.Request(filepath_or_buffer, headers=storage_options) --> 384 with urlopen(req_info) as req: 385 content_encoding = req.headers.get("Content-Encoding", None) 386 if content_encoding == "gzip": 387 # Override compression based on Content-Encoding header File /usr/lib/python3/dist-packages/pandas/io/common.py:289, in urlopen(*args, **kwargs) 283 """ 284 Lazy-import wrapper for stdlib urlopen, as that imports a big chunk of 285 the stdlib. 286 """ 287 import urllib.request --> 289 return urllib.request.urlopen(*args, **kwargs) File /usr/lib/python3.13/urllib/request.py:189, in urlopen(url, data, timeout, context) 187 else: 188 opener = _opener --> 189 return opener.open(url, data, timeout) File /usr/lib/python3.13/urllib/request.py:489, in OpenerDirector.open(self, fullurl, data, timeout) 486 req = meth(req) 488 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method()) --> 489 response = self._open(req, data) 491 # post-process response 492 meth_name = protocol+"_response" File /usr/lib/python3.13/urllib/request.py:506, in OpenerDirector._open(self, req, data) 503 return result 505 protocol = req.type --> 506 result = self._call_chain(self.handle_open, protocol, protocol + 507 '_open', req) 508 if result: 509 return result File /usr/lib/python3.13/urllib/request.py:466, in OpenerDirector._call_chain(self, chain, kind, meth_name, *args) 464 for handler in handlers: 465 func = getattr(handler, meth_name) --> 466 result = func(*args) 467 if result is not None: 468 return result File /usr/lib/python3.13/urllib/request.py:1367, in HTTPSHandler.https_open(self, req) 1366 def https_open(self, req): -> 1367 return self.do_open(http.client.HTTPSConnection, req, 1368 context=self._context) File /usr/lib/python3.13/urllib/request.py:1322, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error -> 1322 raise URLError(err) 1323 r = h.getresponse() 1324 except: URLError: An error occurred while executing the following cell: ------------------ import pandas as pd url = "https://stats.idre.ucla.edu/stat/data/hsb2.csv" hsb2 = pd.read_table(url, delimiter=",") ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3.13/urllib/request.py:1319, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1318 try: -> 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error File /usr/lib/python3.13/http/client.py:1338, in HTTPConnection.request(self, method, url, body, headers, encode_chunked) 1337 """Send a complete request to the server.""" -> 1338 self._send_request(method, url, body, headers, encode_chunked) File /usr/lib/python3.13/http/client.py:1384, in HTTPConnection._send_request(self, method, url, body, headers, encode_chunked) 1383 body = _encode(body, 'body') -> 1384 self.endheaders(body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1333, in HTTPConnection.endheaders(self, message_body, encode_chunked) 1332 raise CannotSendHeader() -> 1333 self._send_output(message_body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1093, in HTTPConnection._send_output(self, message_body, encode_chunked) 1092 del self._buffer[:] -> 1093 self.send(msg) 1095 if message_body is not None: 1096 1097 # create a consistent interface to message_body File /usr/lib/python3.13/http/client.py:1037, in HTTPConnection.send(self, data) 1036 if self.auto_open: -> 1037 self.connect() 1038 else: File /usr/lib/python3.13/http/client.py:1472, in HTTPSConnection.connect(self) 1470 "Connect to a host on a given (SSL) port." -> 1472 super().connect() 1474 if self._tunnel_host: File /usr/lib/python3.13/http/client.py:1003, in HTTPConnection.connect(self) 1002 sys.audit("http.client.connect", self, self.host, self.port) -> 1003 self.sock = self._create_connection( 1004 (self.host,self.port), self.timeout, self.source_address) 1005 # Might fail in OSs that don't implement TCP_NODELAY File /usr/lib/python3.13/socket.py:864, in create_connection(address, timeout, source_address, all_errors) 863 if not all_errors: --> 864 raise exceptions[0] 865 raise ExceptionGroup("create_connection failed", exceptions) File /usr/lib/python3.13/socket.py:849, in create_connection(address, timeout, source_address, all_errors) 848 sock.bind(source_address) --> 849 sock.connect(sa) 850 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused During handling of the above exception, another exception occurred: URLError Traceback (most recent call last) Cell In[2], line 4 1 import pandas as pd 3 url = "https://stats.idre.ucla.edu/stat/data/hsb2.csv" ----> 4 hsb2 = pd.read_table(url, delimiter=",") File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1405, in read_table(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend) 1392 kwds_defaults = _refine_defaults_read( 1393 dialect, 1394 delimiter, (...) 1401 dtype_backend=dtype_backend, 1402 ) 1403 kwds.update(kwds_defaults) -> 1405 return _read(filepath_or_buffer, kwds) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:620, in _read(filepath_or_buffer, kwds) 617 _validate_names(kwds.get("names", None)) 619 # Create the parser. --> 620 parser = TextFileReader(filepath_or_buffer, **kwds) 622 if chunksize or iterator: 623 return parser File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1620, in TextFileReader.__init__(self, f, engine, **kwds) 1617 self.options["has_index_names"] = kwds["has_index_names"] 1619 self.handles: IOHandles | None = None -> 1620 self._engine = self._make_engine(f, self.engine) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1880, in TextFileReader._make_engine(self, f, engine) 1878 if "b" not in mode: 1879 mode += "b" -> 1880 self.handles = get_handle( 1881 f, 1882 mode, 1883 encoding=self.options.get("encoding", None), 1884 compression=self.options.get("compression", None), 1885 memory_map=self.options.get("memory_map", False), 1886 is_text=is_text, 1887 errors=self.options.get("encoding_errors", "strict"), 1888 storage_options=self.options.get("storage_options", None), 1889 ) 1890 assert self.handles is not None 1891 f = self.handles.handle File /usr/lib/python3/dist-packages/pandas/io/common.py:728, in get_handle(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options) 725 codecs.lookup_error(errors) 727 # open URLs --> 728 ioargs = _get_filepath_or_buffer( 729 path_or_buf, 730 encoding=encoding, 731 compression=compression, 732 mode=mode, 733 storage_options=storage_options, 734 ) 736 handle = ioargs.filepath_or_buffer 737 handles: list[BaseBuffer] File /usr/lib/python3/dist-packages/pandas/io/common.py:384, in _get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode, storage_options) 382 # assuming storage_options is to be interpreted as headers 383 req_info = urllib.request.Request(filepath_or_buffer, headers=storage_options) --> 384 with urlopen(req_info) as req: 385 content_encoding = req.headers.get("Content-Encoding", None) 386 if content_encoding == "gzip": 387 # Override compression based on Content-Encoding header File /usr/lib/python3/dist-packages/pandas/io/common.py:289, in urlopen(*args, **kwargs) 283 """ 284 Lazy-import wrapper for stdlib urlopen, as that imports a big chunk of 285 the stdlib. 286 """ 287 import urllib.request --> 289 return urllib.request.urlopen(*args, **kwargs) File /usr/lib/python3.13/urllib/request.py:189, in urlopen(url, data, timeout, context) 187 else: 188 opener = _opener --> 189 return opener.open(url, data, timeout) File /usr/lib/python3.13/urllib/request.py:489, in OpenerDirector.open(self, fullurl, data, timeout) 486 req = meth(req) 488 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method()) --> 489 response = self._open(req, data) 491 # post-process response 492 meth_name = protocol+"_response" File /usr/lib/python3.13/urllib/request.py:506, in OpenerDirector._open(self, req, data) 503 return result 505 protocol = req.type --> 506 result = self._call_chain(self.handle_open, protocol, protocol + 507 '_open', req) 508 if result: 509 return result File /usr/lib/python3.13/urllib/request.py:466, in OpenerDirector._call_chain(self, chain, kind, meth_name, *args) 464 for handler in handlers: 465 func = getattr(handler, meth_name) --> 466 result = func(*args) 467 if result is not None: 468 return result File /usr/lib/python3.13/urllib/request.py:1367, in HTTPSHandler.https_open(self, req) 1366 def https_open(self, req): -> 1367 return self.do_open(http.client.HTTPSConnection, req, 1368 context=self._context) File /usr/lib/python3.13/urllib/request.py:1322, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error -> 1322 raise URLError(err) 1323 r = h.getresponse() 1324 except: URLError: ****************************************************************************** Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/mstl_decomposition.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/mstl_decomposition.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/formulas.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/formulas.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/recursive_ls.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/recursive_ls.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_local_linear_trend.ipynb An error occurred while executing the following cell: ------------------ from io import BytesIO from zipfile import ZipFile import requests # Download the dataset df = pd.read_table( "https://raw.githubusercontent.com/statsmodels/smdatasets/refs/heads/main/data/statespace-local-linear-trend/NorwayFinland.txt", skiprows=1, header=None, sep=r"\s+", engine="python", names=["date", "nf", "ff"], ) ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3.13/urllib/request.py:1319, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1318 try: -> 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error File /usr/lib/python3.13/http/client.py:1338, in HTTPConnection.request(self, method, url, body, headers, encode_chunked) 1337 """Send a complete request to the server.""" -> 1338 self._send_request(method, url, body, headers, encode_chunked) File /usr/lib/python3.13/http/client.py:1384, in HTTPConnection._send_request(self, method, url, body, headers, encode_chunked) 1383 body = _encode(body, 'body') -> 1384 self.endheaders(body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1333, in HTTPConnection.endheaders(self, message_body, encode_chunked) 1332 raise CannotSendHeader() -> 1333 self._send_output(message_body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1093, in HTTPConnection._send_output(self, message_body, encode_chunked) 1092 del self._buffer[:] -> 1093 self.send(msg) 1095 if message_body is not None: 1096 1097 # create a consistent interface to message_body File /usr/lib/python3.13/http/client.py:1037, in HTTPConnection.send(self, data) 1036 if self.auto_open: -> 1037 self.connect() 1038 else: File /usr/lib/python3.13/http/client.py:1472, in HTTPSConnection.connect(self) 1470 "Connect to a host on a given (SSL) port." -> 1472 super().connect() 1474 if self._tunnel_host: File /usr/lib/python3.13/http/client.py:1003, in HTTPConnection.connect(self) 1002 sys.audit("http.client.connect", self, self.host, self.port) -> 1003 self.sock = self._create_connection( 1004 (self.host,self.port), self.timeout, self.source_address) 1005 # Might fail in OSs that don't implement TCP_NODELAY File /usr/lib/python3.13/socket.py:864, in create_connection(address, timeout, source_address, all_errors) 863 if not all_errors: --> 864 raise exceptions[0] 865 raise ExceptionGroup("create_connection failed", exceptions) File /usr/lib/python3.13/socket.py:849, in create_connection(address, timeout, source_address, all_errors) 848 sock.bind(source_address) --> 849 sock.connect(sa) 850 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused During handling of the above exception, another exception occurred: URLError Traceback (most recent call last) Cell In[3], line 7 4 import requests 6 # Download the dataset ----> 7 df = pd.read_table( 8 "https://raw.githubusercontent.com/statsmodels/smdatasets/refs/heads/main/data/statespace-local-linear-trend/NorwayFinland.txt", 9 skiprows=1, 10 header=None, 11 sep=r"\s+", 12 engine="python", 13 names=["date", "nf", "ff"], 14 ) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1405, in read_table(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend) 1392 kwds_defaults = _refine_defaults_read( 1393 dialect, 1394 delimiter, (...) 1401 dtype_backend=dtype_backend, 1402 ) 1403 kwds.update(kwds_defaults) -> 1405 return _read(filepath_or_buffer, kwds) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:620, in _read(filepath_or_buffer, kwds) 617 _validate_names(kwds.get("names", None)) 619 # Create the parser. --> 620 parser = TextFileReader(filepath_or_buffer, **kwds) 622 if chunksize or iterator: 623 return parser File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1620, in TextFileReader.__init__(self, f, engine, **kwds) 1617 self.options["has_index_names"] = kwds["has_index_names"] 1619 self.handles: IOHandles | None = None -> 1620 self._engine = self._make_engine(f, self.engine) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1880, in TextFileReader._make_engine(self, f, engine) 1878 if "b" not in mode: 1879 mode += "b" -> 1880 self.handles = get_handle( 1881 f, 1882 mode, 1883 encoding=self.options.get("encoding", None), 1884 compression=self.options.get("compression", None), 1885 memory_map=self.options.get("memory_map", False), 1886 is_text=is_text, 1887 errors=self.options.get("encoding_errors", "strict"), 1888 storage_options=self.options.get("storage_options", None), 1889 ) 1890 assert self.handles is not None 1891 f = self.handles.handle File /usr/lib/python3/dist-packages/pandas/io/common.py:728, in get_handle(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options) 725 codecs.lookup_error(errors) 727 # open URLs --> 728 ioargs = _get_filepath_or_buffer( 729 path_or_buf, 730 encoding=encoding, 731 compression=compression, 732 mode=mode, 733 storage_options=storage_options, 734 ) 736 handle = ioargs.filepath_or_buffer 737 handles: list[BaseBuffer] File /usr/lib/python3/dist-packages/pandas/io/common.py:384, in _get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode, storage_options) 382 # assuming storage_options is to be interpreted as headers 383 req_info = urllib.request.Request(filepath_or_buffer, headers=storage_options) --> 384 with urlopen(req_info) as req: 385 content_encoding = req.headers.get("Content-Encoding", None) 386 if content_encoding == "gzip": 387 # Override compression based on Content-Encoding header File /usr/lib/python3/dist-packages/pandas/io/common.py:289, in urlopen(*args, **kwargs) 283 """ 284 Lazy-import wrapper for stdlib urlopen, as that imports a big chunk of 285 the stdlib. 286 """ 287 import urllib.request --> 289 return urllib.request.urlopen(*args, **kwargs) File /usr/lib/python3.13/urllib/request.py:189, in urlopen(url, data, timeout, context) 187 else: 188 opener = _opener --> 189 return opener.open(url, data, timeout) File /usr/lib/python3.13/urllib/request.py:489, in OpenerDirector.open(self, fullurl, data, timeout) 486 req = meth(req) 488 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method()) --> 489 response = self._open(req, data) 491 # post-process response 492 meth_name = protocol+"_response" File /usr/lib/python3.13/urllib/request.py:506, in OpenerDirector._open(self, req, data) 503 return result 505 protocol = req.type --> 506 result = self._call_chain(self.handle_open, protocol, protocol + 507 '_open', req) 508 if result: 509 return result File /usr/lib/python3.13/urllib/request.py:466, in OpenerDirector._call_chain(self, chain, kind, meth_name, *args) 464 for handler in handlers: 465 func = getattr(handler, meth_name) --> 466 result = func(*args) 467 if result is not None: 468 return result File /usr/lib/python3.13/urllib/request.py:1367, in HTTPSHandler.https_open(self, req) 1366 def https_open(self, req): -> 1367 return self.do_open(http.client.HTTPSConnection, req, 1368 context=self._context) File /usr/lib/python3.13/urllib/request.py:1322, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error -> 1322 raise URLError(err) 1323 r = h.getresponse() 1324 except: URLError: An error occurred while executing the following cell: ------------------ from io import BytesIO from zipfile import ZipFile import requests # Download the dataset df = pd.read_table( "https://raw.githubusercontent.com/statsmodels/smdatasets/refs/heads/main/data/statespace-local-linear-trend/NorwayFinland.txt", skiprows=1, header=None, sep=r"\s+", engine="python", names=["date", "nf", "ff"], ) ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3.13/urllib/request.py:1319, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1318 try: -> 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error File /usr/lib/python3.13/http/client.py:1338, in HTTPConnection.request(self, method, url, body, headers, encode_chunked) 1337 """Send a complete request to the server.""" -> 1338 self._send_request(method, url, body, headers, encode_chunked) File /usr/lib/python3.13/http/client.py:1384, in HTTPConnection._send_request(self, method, url, body, headers, encode_chunked) 1383 body = _encode(body, 'body') -> 1384 self.endheaders(body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1333, in HTTPConnection.endheaders(self, message_body, encode_chunked) 1332 raise CannotSendHeader() -> 1333 self._send_output(message_body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1093, in HTTPConnection._send_output(self, message_body, encode_chunked) 1092 del self._buffer[:] -> 1093 self.send(msg) 1095 if message_body is not None: 1096 1097 # create a consistent interface to message_body File /usr/lib/python3.13/http/client.py:1037, in HTTPConnection.send(self, data) 1036 if self.auto_open: -> 1037 self.connect() 1038 else: File /usr/lib/python3.13/http/client.py:1472, in HTTPSConnection.connect(self) 1470 "Connect to a host on a given (SSL) port." -> 1472 super().connect() 1474 if self._tunnel_host: File /usr/lib/python3.13/http/client.py:1003, in HTTPConnection.connect(self) 1002 sys.audit("http.client.connect", self, self.host, self.port) -> 1003 self.sock = self._create_connection( 1004 (self.host,self.port), self.timeout, self.source_address) 1005 # Might fail in OSs that don't implement TCP_NODELAY File /usr/lib/python3.13/socket.py:864, in create_connection(address, timeout, source_address, all_errors) 863 if not all_errors: --> 864 raise exceptions[0] 865 raise ExceptionGroup("create_connection failed", exceptions) File /usr/lib/python3.13/socket.py:849, in create_connection(address, timeout, source_address, all_errors) 848 sock.bind(source_address) --> 849 sock.connect(sa) 850 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused During handling of the above exception, another exception occurred: URLError Traceback (most recent call last) Cell In[3], line 7 4 import requests 6 # Download the dataset ----> 7 df = pd.read_table( 8 "https://raw.githubusercontent.com/statsmodels/smdatasets/refs/heads/main/data/statespace-local-linear-trend/NorwayFinland.txt", 9 skiprows=1, 10 header=None, 11 sep=r"\s+", 12 engine="python", 13 names=["date", "nf", "ff"], 14 ) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1405, in read_table(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend) 1392 kwds_defaults = _refine_defaults_read( 1393 dialect, 1394 delimiter, (...) 1401 dtype_backend=dtype_backend, 1402 ) 1403 kwds.update(kwds_defaults) -> 1405 return _read(filepath_or_buffer, kwds) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:620, in _read(filepath_or_buffer, kwds) 617 _validate_names(kwds.get("names", None)) 619 # Create the parser. --> 620 parser = TextFileReader(filepath_or_buffer, **kwds) 622 if chunksize or iterator: 623 return parser File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1620, in TextFileReader.__init__(self, f, engine, **kwds) 1617 self.options["has_index_names"] = kwds["has_index_names"] 1619 self.handles: IOHandles | None = None -> 1620 self._engine = self._make_engine(f, self.engine) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1880, in TextFileReader._make_engine(self, f, engine) 1878 if "b" not in mode: 1879 mode += "b" -> 1880 self.handles = get_handle( 1881 f, 1882 mode, 1883 encoding=self.options.get("encoding", None), 1884 compression=self.options.get("compression", None), 1885 memory_map=self.options.get("memory_map", False), 1886 is_text=is_text, 1887 errors=self.options.get("encoding_errors", "strict"), 1888 storage_options=self.options.get("storage_options", None), 1889 ) 1890 assert self.handles is not None 1891 f = self.handles.handle File /usr/lib/python3/dist-packages/pandas/io/common.py:728, in get_handle(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options) 725 codecs.lookup_error(errors) 727 # open URLs --> 728 ioargs = _get_filepath_or_buffer( 729 path_or_buf, 730 encoding=encoding, 731 compression=compression, 732 mode=mode, 733 storage_options=storage_options, 734 ) 736 handle = ioargs.filepath_or_buffer 737 handles: list[BaseBuffer] File /usr/lib/python3/dist-packages/pandas/io/common.py:384, in _get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode, storage_options) 382 # assuming storage_options is to be interpreted as headers 383 req_info = urllib.request.Request(filepath_or_buffer, headers=storage_options) --> 384 with urlopen(req_info) as req: 385 content_encoding = req.headers.get("Content-Encoding", None) 386 if content_encoding == "gzip": 387 # Override compression based on Content-Encoding header File /usr/lib/python3/dist-packages/pandas/io/common.py:289, in urlopen(*args, **kwargs) 283 """ 284 Lazy-import wrapper for stdlib urlopen, as that imports a big chunk of 285 the stdlib. 286 """ 287 import urllib.request --> 289 return urllib.request.urlopen(*args, **kwargs) File /usr/lib/python3.13/urllib/request.py:189, in urlopen(url, data, timeout, context) 187 else: 188 opener = _opener --> 189 return opener.open(url, data, timeout) File /usr/lib/python3.13/urllib/request.py:489, in OpenerDirector.open(self, fullurl, data, timeout) 486 req = meth(req) 488 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method()) --> 489 response = self._open(req, data) 491 # post-process response 492 meth_name = protocol+"_response" File /usr/lib/python3.13/urllib/request.py:506, in OpenerDirector._open(self, req, data) 503 return result 505 protocol = req.type --> 506 result = self._call_chain(self.handle_open, protocol, protocol + 507 '_open', req) 508 if result: 509 return result File /usr/lib/python3.13/urllib/request.py:466, in OpenerDirector._call_chain(self, chain, kind, meth_name, *args) 464 for handler in handlers: 465 func = getattr(handler, meth_name) --> 466 result = func(*args) 467 if result is not None: 468 return result File /usr/lib/python3.13/urllib/request.py:1367, in HTTPSHandler.https_open(self, req) 1366 def https_open(self, req): -> 1367 return self.do_open(http.client.HTTPSConnection, req, 1368 context=self._context) File /usr/lib/python3.13/urllib/request.py:1322, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error -> 1322 raise URLError(err) 1323 r = h.getresponse() 1324 except: URLError: ****************************************************************************** Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/ols.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/ols.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/pca_fertility_factors.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/pca_fertility_factors.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_structural_harvey_jaeger.ipynb An error occurred while executing the following cell: ------------------ # Datasets from pandas_datareader.data import DataReader # Get the raw data start = '1948-01' end = '2008-01' us_gnp = DataReader('GNPC96', 'fred', start=start, end=end) us_gnp_deflator = DataReader('GNPDEF', 'fred', start=start, end=end) us_monetary_base = DataReader('AMBSL', 'fred', start=start, end=end).resample('QS').mean() recessions = DataReader('USRECQ', 'fred', start=start, end=end).resample('QS').last().values[:,0] # Construct the dataframe dta = pd.concat(map(np.log, (us_gnp, us_gnp_deflator, us_monetary_base)), axis=1) dta.columns = ['US GNP','US Prices','US monetary base'] dta.index.freq = dta.index.inferred_freq dates = dta.index._mpl_repr() ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[2], line 2 1 # Datasets ----> 2 from pandas_datareader.data import DataReader 4 # Get the raw data 5 start = '1948-01' ModuleNotFoundError: No module named 'pandas_datareader' An error occurred while executing the following cell: ------------------ # Datasets from pandas_datareader.data import DataReader # Get the raw data start = '1948-01' end = '2008-01' us_gnp = DataReader('GNPC96', 'fred', start=start, end=end) us_gnp_deflator = DataReader('GNPDEF', 'fred', start=start, end=end) us_monetary_base = DataReader('AMBSL', 'fred', start=start, end=end).resample('QS').mean() recessions = DataReader('USRECQ', 'fred', start=start, end=end).resample('QS').last().values[:,0] # Construct the dataframe dta = pd.concat(map(np.log, (us_gnp, us_gnp_deflator, us_monetary_base)), axis=1) dta.columns = ['US GNP','US Prices','US monetary base'] dta.index.freq = dta.index.inferred_freq dates = dta.index._mpl_repr() ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[2], line 2 1 # Datasets ----> 2 from pandas_datareader.data import DataReader 4 # Get the raw data 5 start = '1948-01' ModuleNotFoundError: No module named 'pandas_datareader' ****************************************************************************** Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/markov_autoregression.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/markov_autoregression.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/stats_rankcompare.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/stats_rankcompare.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/discrete_choice_example.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/discrete_choice_example.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/gee_score_test_simulation.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/gee_score_test_simulation.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/kernel_density.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/kernel_density.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/recursive_ls.ipynb An error occurred while executing the following cell: ------------------ %matplotlib inline import matplotlib.pyplot as plt import numpy as np import pandas as pd import statsmodels.api as sm from pandas_datareader.data import DataReader np.set_printoptions(suppress=True) ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 6 4 import pandas as pd 5 import statsmodels.api as sm ----> 6 from pandas_datareader.data import DataReader 8 np.set_printoptions(suppress=True) ModuleNotFoundError: No module named 'pandas_datareader' An error occurred while executing the following cell: ------------------ %matplotlib inline import matplotlib.pyplot as plt import numpy as np import pandas as pd import statsmodels.api as sm from pandas_datareader.data import DataReader np.set_printoptions(suppress=True) ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 6 4 import pandas as pd 5 import statsmodels.api as sm ----> 6 from pandas_datareader.data import DataReader 8 np.set_printoptions(suppress=True) ModuleNotFoundError: No module named 'pandas_datareader' ****************************************************************************** Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_sarimax_internet.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_sarimax_internet.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_sarimax_stata.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_sarimax_stata.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/quantile_regression.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/quantile_regression.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/gee_nested_simulation.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/gee_nested_simulation.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/markov_autoregression.ipynb An error occurred while executing the following cell: ------------------ %matplotlib inline from datetime import datetime from io import BytesIO import matplotlib.pyplot as plt import numpy as np import pandas as pd import requests import statsmodels.api as sm # NBER recessions from pandas_datareader.data import DataReader usrec = DataReader( "USREC", "fred", start=datetime(1947, 1, 1), end=datetime(2013, 4, 1) ) ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 13 10 import statsmodels.api as sm 12 # NBER recessions ---> 13 from pandas_datareader.data import DataReader 15 usrec = DataReader( 16 "USREC", "fred", start=datetime(1947, 1, 1), end=datetime(2013, 4, 1) 17 ) ModuleNotFoundError: No module named 'pandas_datareader' An error occurred while executing the following cell: ------------------ %matplotlib inline from datetime import datetime from io import BytesIO import matplotlib.pyplot as plt import numpy as np import pandas as pd import requests import statsmodels.api as sm # NBER recessions from pandas_datareader.data import DataReader usrec = DataReader( "USREC", "fred", start=datetime(1947, 1, 1), end=datetime(2013, 4, 1) ) ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 13 10 import statsmodels.api as sm 12 # NBER recessions ---> 13 from pandas_datareader.data import DataReader 15 usrec = DataReader( 16 "USREC", "fred", start=datetime(1947, 1, 1), end=datetime(2013, 4, 1) 17 ) ModuleNotFoundError: No module named 'pandas_datareader' ****************************************************************************** Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/ordinal_regression.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/ordinal_regression.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/metaanalysis1.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/metaanalysis1.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/regression_plots.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/regression_plots.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/tsa_dates.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/tsa_dates.ipynb Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/theta-model.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/theta-model.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/mstl_decomposition.ipynb An error occurred while executing the following cell: ------------------ url = "https://raw.githubusercontent.com/tidyverts/tsibbledata/master/data-raw/vic_elec/VIC2015/demand.csv" df = pd.read_csv(url) ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3.13/urllib/request.py:1319, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1318 try: -> 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error File /usr/lib/python3.13/http/client.py:1338, in HTTPConnection.request(self, method, url, body, headers, encode_chunked) 1337 """Send a complete request to the server.""" -> 1338 self._send_request(method, url, body, headers, encode_chunked) File /usr/lib/python3.13/http/client.py:1384, in HTTPConnection._send_request(self, method, url, body, headers, encode_chunked) 1383 body = _encode(body, 'body') -> 1384 self.endheaders(body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1333, in HTTPConnection.endheaders(self, message_body, encode_chunked) 1332 raise CannotSendHeader() -> 1333 self._send_output(message_body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1093, in HTTPConnection._send_output(self, message_body, encode_chunked) 1092 del self._buffer[:] -> 1093 self.send(msg) 1095 if message_body is not None: 1096 1097 # create a consistent interface to message_body File /usr/lib/python3.13/http/client.py:1037, in HTTPConnection.send(self, data) 1036 if self.auto_open: -> 1037 self.connect() 1038 else: File /usr/lib/python3.13/http/client.py:1472, in HTTPSConnection.connect(self) 1470 "Connect to a host on a given (SSL) port." -> 1472 super().connect() 1474 if self._tunnel_host: File /usr/lib/python3.13/http/client.py:1003, in HTTPConnection.connect(self) 1002 sys.audit("http.client.connect", self, self.host, self.port) -> 1003 self.sock = self._create_connection( 1004 (self.host,self.port), self.timeout, self.source_address) 1005 # Might fail in OSs that don't implement TCP_NODELAY File /usr/lib/python3.13/socket.py:864, in create_connection(address, timeout, source_address, all_errors) 863 if not all_errors: --> 864 raise exceptions[0] 865 raise ExceptionGroup("create_connection failed", exceptions) File /usr/lib/python3.13/socket.py:849, in create_connection(address, timeout, source_address, all_errors) 848 sock.bind(source_address) --> 849 sock.connect(sa) 850 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused During handling of the above exception, another exception occurred: URLError Traceback (most recent call last) Cell In[10], line 2 1 url = "https://raw.githubusercontent.com/tidyverts/tsibbledata/master/data-raw/vic_elec/VIC2015/demand.csv" ----> 2 df = pd.read_csv(url) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1026, in read_csv(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend) 1013 kwds_defaults = _refine_defaults_read( 1014 dialect, 1015 delimiter, (...) 1022 dtype_backend=dtype_backend, 1023 ) 1024 kwds.update(kwds_defaults) -> 1026 return _read(filepath_or_buffer, kwds) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:620, in _read(filepath_or_buffer, kwds) 617 _validate_names(kwds.get("names", None)) 619 # Create the parser. --> 620 parser = TextFileReader(filepath_or_buffer, **kwds) 622 if chunksize or iterator: 623 return parser File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1620, in TextFileReader.__init__(self, f, engine, **kwds) 1617 self.options["has_index_names"] = kwds["has_index_names"] 1619 self.handles: IOHandles | None = None -> 1620 self._engine = self._make_engine(f, self.engine) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1880, in TextFileReader._make_engine(self, f, engine) 1878 if "b" not in mode: 1879 mode += "b" -> 1880 self.handles = get_handle( 1881 f, 1882 mode, 1883 encoding=self.options.get("encoding", None), 1884 compression=self.options.get("compression", None), 1885 memory_map=self.options.get("memory_map", False), 1886 is_text=is_text, 1887 errors=self.options.get("encoding_errors", "strict"), 1888 storage_options=self.options.get("storage_options", None), 1889 ) 1890 assert self.handles is not None 1891 f = self.handles.handle File /usr/lib/python3/dist-packages/pandas/io/common.py:728, in get_handle(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options) 725 codecs.lookup_error(errors) 727 # open URLs --> 728 ioargs = _get_filepath_or_buffer( 729 path_or_buf, 730 encoding=encoding, 731 compression=compression, 732 mode=mode, 733 storage_options=storage_options, 734 ) 736 handle = ioargs.filepath_or_buffer 737 handles: list[BaseBuffer] File /usr/lib/python3/dist-packages/pandas/io/common.py:384, in _get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode, storage_options) 382 # assuming storage_options is to be interpreted as headers 383 req_info = urllib.request.Request(filepath_or_buffer, headers=storage_options) --> 384 with urlopen(req_info) as req: 385 content_encoding = req.headers.get("Content-Encoding", None) 386 if content_encoding == "gzip": 387 # Override compression based on Content-Encoding header File /usr/lib/python3/dist-packages/pandas/io/common.py:289, in urlopen(*args, **kwargs) 283 """ 284 Lazy-import wrapper for stdlib urlopen, as that imports a big chunk of 285 the stdlib. 286 """ 287 import urllib.request --> 289 return urllib.request.urlopen(*args, **kwargs) File /usr/lib/python3.13/urllib/request.py:189, in urlopen(url, data, timeout, context) 187 else: 188 opener = _opener --> 189 return opener.open(url, data, timeout) File /usr/lib/python3.13/urllib/request.py:489, in OpenerDirector.open(self, fullurl, data, timeout) 486 req = meth(req) 488 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method()) --> 489 response = self._open(req, data) 491 # post-process response 492 meth_name = protocol+"_response" File /usr/lib/python3.13/urllib/request.py:506, in OpenerDirector._open(self, req, data) 503 return result 505 protocol = req.type --> 506 result = self._call_chain(self.handle_open, protocol, protocol + 507 '_open', req) 508 if result: 509 return result File /usr/lib/python3.13/urllib/request.py:466, in OpenerDirector._call_chain(self, chain, kind, meth_name, *args) 464 for handler in handlers: 465 func = getattr(handler, meth_name) --> 466 result = func(*args) 467 if result is not None: 468 return result File /usr/lib/python3.13/urllib/request.py:1367, in HTTPSHandler.https_open(self, req) 1366 def https_open(self, req): -> 1367 return self.do_open(http.client.HTTPSConnection, req, 1368 context=self._context) File /usr/lib/python3.13/urllib/request.py:1322, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error -> 1322 raise URLError(err) 1323 r = h.getresponse() 1324 except: URLError: An error occurred while executing the following cell: ------------------ url = "https://raw.githubusercontent.com/tidyverts/tsibbledata/master/data-raw/vic_elec/VIC2015/demand.csv" df = pd.read_csv(url) ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3.13/urllib/request.py:1319, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1318 try: -> 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error File /usr/lib/python3.13/http/client.py:1338, in HTTPConnection.request(self, method, url, body, headers, encode_chunked) 1337 """Send a complete request to the server.""" -> 1338 self._send_request(method, url, body, headers, encode_chunked) File /usr/lib/python3.13/http/client.py:1384, in HTTPConnection._send_request(self, method, url, body, headers, encode_chunked) 1383 body = _encode(body, 'body') -> 1384 self.endheaders(body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1333, in HTTPConnection.endheaders(self, message_body, encode_chunked) 1332 raise CannotSendHeader() -> 1333 self._send_output(message_body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1093, in HTTPConnection._send_output(self, message_body, encode_chunked) 1092 del self._buffer[:] -> 1093 self.send(msg) 1095 if message_body is not None: 1096 1097 # create a consistent interface to message_body File /usr/lib/python3.13/http/client.py:1037, in HTTPConnection.send(self, data) 1036 if self.auto_open: -> 1037 self.connect() 1038 else: File /usr/lib/python3.13/http/client.py:1472, in HTTPSConnection.connect(self) 1470 "Connect to a host on a given (SSL) port." -> 1472 super().connect() 1474 if self._tunnel_host: File /usr/lib/python3.13/http/client.py:1003, in HTTPConnection.connect(self) 1002 sys.audit("http.client.connect", self, self.host, self.port) -> 1003 self.sock = self._create_connection( 1004 (self.host,self.port), self.timeout, self.source_address) 1005 # Might fail in OSs that don't implement TCP_NODELAY File /usr/lib/python3.13/socket.py:864, in create_connection(address, timeout, source_address, all_errors) 863 if not all_errors: --> 864 raise exceptions[0] 865 raise ExceptionGroup("create_connection failed", exceptions) File /usr/lib/python3.13/socket.py:849, in create_connection(address, timeout, source_address, all_errors) 848 sock.bind(source_address) --> 849 sock.connect(sa) 850 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused During handling of the above exception, another exception occurred: URLError Traceback (most recent call last) Cell In[10], line 2 1 url = "https://raw.githubusercontent.com/tidyverts/tsibbledata/master/data-raw/vic_elec/VIC2015/demand.csv" ----> 2 df = pd.read_csv(url) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1026, in read_csv(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend) 1013 kwds_defaults = _refine_defaults_read( 1014 dialect, 1015 delimiter, (...) 1022 dtype_backend=dtype_backend, 1023 ) 1024 kwds.update(kwds_defaults) -> 1026 return _read(filepath_or_buffer, kwds) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:620, in _read(filepath_or_buffer, kwds) 617 _validate_names(kwds.get("names", None)) 619 # Create the parser. --> 620 parser = TextFileReader(filepath_or_buffer, **kwds) 622 if chunksize or iterator: 623 return parser File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1620, in TextFileReader.__init__(self, f, engine, **kwds) 1617 self.options["has_index_names"] = kwds["has_index_names"] 1619 self.handles: IOHandles | None = None -> 1620 self._engine = self._make_engine(f, self.engine) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1880, in TextFileReader._make_engine(self, f, engine) 1878 if "b" not in mode: 1879 mode += "b" -> 1880 self.handles = get_handle( 1881 f, 1882 mode, 1883 encoding=self.options.get("encoding", None), 1884 compression=self.options.get("compression", None), 1885 memory_map=self.options.get("memory_map", False), 1886 is_text=is_text, 1887 errors=self.options.get("encoding_errors", "strict"), 1888 storage_options=self.options.get("storage_options", None), 1889 ) 1890 assert self.handles is not None 1891 f = self.handles.handle File /usr/lib/python3/dist-packages/pandas/io/common.py:728, in get_handle(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options) 725 codecs.lookup_error(errors) 727 # open URLs --> 728 ioargs = _get_filepath_or_buffer( 729 path_or_buf, 730 encoding=encoding, 731 compression=compression, 732 mode=mode, 733 storage_options=storage_options, 734 ) 736 handle = ioargs.filepath_or_buffer 737 handles: list[BaseBuffer] File /usr/lib/python3/dist-packages/pandas/io/common.py:384, in _get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode, storage_options) 382 # assuming storage_options is to be interpreted as headers 383 req_info = urllib.request.Request(filepath_or_buffer, headers=storage_options) --> 384 with urlopen(req_info) as req: 385 content_encoding = req.headers.get("Content-Encoding", None) 386 if content_encoding == "gzip": 387 # Override compression based on Content-Encoding header File /usr/lib/python3/dist-packages/pandas/io/common.py:289, in urlopen(*args, **kwargs) 283 """ 284 Lazy-import wrapper for stdlib urlopen, as that imports a big chunk of 285 the stdlib. 286 """ 287 import urllib.request --> 289 return urllib.request.urlopen(*args, **kwargs) File /usr/lib/python3.13/urllib/request.py:189, in urlopen(url, data, timeout, context) 187 else: 188 opener = _opener --> 189 return opener.open(url, data, timeout) File /usr/lib/python3.13/urllib/request.py:489, in OpenerDirector.open(self, fullurl, data, timeout) 486 req = meth(req) 488 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method()) --> 489 response = self._open(req, data) 491 # post-process response 492 meth_name = protocol+"_response" File /usr/lib/python3.13/urllib/request.py:506, in OpenerDirector._open(self, req, data) 503 return result 505 protocol = req.type --> 506 result = self._call_chain(self.handle_open, protocol, protocol + 507 '_open', req) 508 if result: 509 return result File /usr/lib/python3.13/urllib/request.py:466, in OpenerDirector._call_chain(self, chain, kind, meth_name, *args) 464 for handler in handlers: 465 func = getattr(handler, meth_name) --> 466 result = func(*args) 467 if result is not None: 468 return result File /usr/lib/python3.13/urllib/request.py:1367, in HTTPSHandler.https_open(self, req) 1366 def https_open(self, req): -> 1367 return self.do_open(http.client.HTTPSConnection, req, 1368 context=self._context) File /usr/lib/python3.13/urllib/request.py:1322, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error -> 1322 raise URLError(err) 1323 r = h.getresponse() 1324 except: URLError: ****************************************************************************** Executing /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/rolling_ls.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/rolling_ls.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_sarimax_internet.ipynb An error occurred while executing the following cell: ------------------ import requests from io import BytesIO from zipfile import ZipFile # Download the dataset df = pd.read_table( "https://raw.githubusercontent.com/jrnold/ssmodels-in-stan/master/StanStateSpace/data-raw/DK-data/internet.dat", skiprows=1, header=None, sep='\s+', engine='python', names=['internet','dinternet'] ) ------------------ ----- stderr ----- <>:8: SyntaxWarning: invalid escape sequence '\s' <>:8: SyntaxWarning: invalid escape sequence '\s' /tmp/ipykernel_4746/1758367982.py:8: SyntaxWarning: invalid escape sequence '\s' skiprows=1, header=None, sep='\s+', engine='python', ----- stderr ----- /tmp/ipykernel_4746/1758367982.py:8: SyntaxWarning: invalid escape sequence '\s' skiprows=1, header=None, sep='\s+', engine='python', ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3.13/urllib/request.py:1319, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1318 try: -> 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error File /usr/lib/python3.13/http/client.py:1338, in HTTPConnection.request(self, method, url, body, headers, encode_chunked) 1337 """Send a complete request to the server.""" -> 1338 self._send_request(method, url, body, headers, encode_chunked) File /usr/lib/python3.13/http/client.py:1384, in HTTPConnection._send_request(self, method, url, body, headers, encode_chunked) 1383 body = _encode(body, 'body') -> 1384 self.endheaders(body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1333, in HTTPConnection.endheaders(self, message_body, encode_chunked) 1332 raise CannotSendHeader() -> 1333 self._send_output(message_body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1093, in HTTPConnection._send_output(self, message_body, encode_chunked) 1092 del self._buffer[:] -> 1093 self.send(msg) 1095 if message_body is not None: 1096 1097 # create a consistent interface to message_body File /usr/lib/python3.13/http/client.py:1037, in HTTPConnection.send(self, data) 1036 if self.auto_open: -> 1037 self.connect() 1038 else: File /usr/lib/python3.13/http/client.py:1472, in HTTPSConnection.connect(self) 1470 "Connect to a host on a given (SSL) port." -> 1472 super().connect() 1474 if self._tunnel_host: File /usr/lib/python3.13/http/client.py:1003, in HTTPConnection.connect(self) 1002 sys.audit("http.client.connect", self, self.host, self.port) -> 1003 self.sock = self._create_connection( 1004 (self.host,self.port), self.timeout, self.source_address) 1005 # Might fail in OSs that don't implement TCP_NODELAY File /usr/lib/python3.13/socket.py:864, in create_connection(address, timeout, source_address, all_errors) 863 if not all_errors: --> 864 raise exceptions[0] 865 raise ExceptionGroup("create_connection failed", exceptions) File /usr/lib/python3.13/socket.py:849, in create_connection(address, timeout, source_address, all_errors) 848 sock.bind(source_address) --> 849 sock.connect(sa) 850 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused During handling of the above exception, another exception occurred: URLError Traceback (most recent call last) Cell In[3], line 6 3 from zipfile import ZipFile 5 # Download the dataset ----> 6 df = pd.read_table( 7 "https://raw.githubusercontent.com/jrnold/ssmodels-in-stan/master/StanStateSpace/data-raw/DK-data/internet.dat", 8 skiprows=1, header=None, sep='\s+', engine='python', 9 names=['internet','dinternet'] 10 ) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1405, in read_table(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend) 1392 kwds_defaults = _refine_defaults_read( 1393 dialect, 1394 delimiter, (...) 1401 dtype_backend=dtype_backend, 1402 ) 1403 kwds.update(kwds_defaults) -> 1405 return _read(filepath_or_buffer, kwds) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:620, in _read(filepath_or_buffer, kwds) 617 _validate_names(kwds.get("names", None)) 619 # Create the parser. --> 620 parser = TextFileReader(filepath_or_buffer, **kwds) 622 if chunksize or iterator: 623 return parser File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1620, in TextFileReader.__init__(self, f, engine, **kwds) 1617 self.options["has_index_names"] = kwds["has_index_names"] 1619 self.handles: IOHandles | None = None -> 1620 self._engine = self._make_engine(f, self.engine) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1880, in TextFileReader._make_engine(self, f, engine) 1878 if "b" not in mode: 1879 mode += "b" -> 1880 self.handles = get_handle( 1881 f, 1882 mode, 1883 encoding=self.options.get("encoding", None), 1884 compression=self.options.get("compression", None), 1885 memory_map=self.options.get("memory_map", False), 1886 is_text=is_text, 1887 errors=self.options.get("encoding_errors", "strict"), 1888 storage_options=self.options.get("storage_options", None), 1889 ) 1890 assert self.handles is not None 1891 f = self.handles.handle File /usr/lib/python3/dist-packages/pandas/io/common.py:728, in get_handle(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options) 725 codecs.lookup_error(errors) 727 # open URLs --> 728 ioargs = _get_filepath_or_buffer( 729 path_or_buf, 730 encoding=encoding, 731 compression=compression, 732 mode=mode, 733 storage_options=storage_options, 734 ) 736 handle = ioargs.filepath_or_buffer 737 handles: list[BaseBuffer] File /usr/lib/python3/dist-packages/pandas/io/common.py:384, in _get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode, storage_options) 382 # assuming storage_options is to be interpreted as headers 383 req_info = urllib.request.Request(filepath_or_buffer, headers=storage_options) --> 384 with urlopen(req_info) as req: 385 content_encoding = req.headers.get("Content-Encoding", None) 386 if content_encoding == "gzip": 387 # Override compression based on Content-Encoding header File /usr/lib/python3/dist-packages/pandas/io/common.py:289, in urlopen(*args, **kwargs) 283 """ 284 Lazy-import wrapper for stdlib urlopen, as that imports a big chunk of 285 the stdlib. 286 """ 287 import urllib.request --> 289 return urllib.request.urlopen(*args, **kwargs) File /usr/lib/python3.13/urllib/request.py:189, in urlopen(url, data, timeout, context) 187 else: 188 opener = _opener --> 189 return opener.open(url, data, timeout) File /usr/lib/python3.13/urllib/request.py:489, in OpenerDirector.open(self, fullurl, data, timeout) 486 req = meth(req) 488 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method()) --> 489 response = self._open(req, data) 491 # post-process response 492 meth_name = protocol+"_response" File /usr/lib/python3.13/urllib/request.py:506, in OpenerDirector._open(self, req, data) 503 return result 505 protocol = req.type --> 506 result = self._call_chain(self.handle_open, protocol, protocol + 507 '_open', req) 508 if result: 509 return result File /usr/lib/python3.13/urllib/request.py:466, in OpenerDirector._call_chain(self, chain, kind, meth_name, *args) 464 for handler in handlers: 465 func = getattr(handler, meth_name) --> 466 result = func(*args) 467 if result is not None: 468 return result File /usr/lib/python3.13/urllib/request.py:1367, in HTTPSHandler.https_open(self, req) 1366 def https_open(self, req): -> 1367 return self.do_open(http.client.HTTPSConnection, req, 1368 context=self._context) File /usr/lib/python3.13/urllib/request.py:1322, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error -> 1322 raise URLError(err) 1323 r = h.getresponse() 1324 except: URLError: An error occurred while executing the following cell: ------------------ import requests from io import BytesIO from zipfile import ZipFile # Download the dataset df = pd.read_table( "https://raw.githubusercontent.com/jrnold/ssmodels-in-stan/master/StanStateSpace/data-raw/DK-data/internet.dat", skiprows=1, header=None, sep='\s+', engine='python', names=['internet','dinternet'] ) ------------------ ----- stderr ----- <>:8: SyntaxWarning: invalid escape sequence '\s' <>:8: SyntaxWarning: invalid escape sequence '\s' /tmp/ipykernel_4746/1758367982.py:8: SyntaxWarning: invalid escape sequence '\s' skiprows=1, header=None, sep='\s+', engine='python', ----- stderr ----- /tmp/ipykernel_4746/1758367982.py:8: SyntaxWarning: invalid escape sequence '\s' skiprows=1, header=None, sep='\s+', engine='python', ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3.13/urllib/request.py:1319, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1318 try: -> 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error File /usr/lib/python3.13/http/client.py:1338, in HTTPConnection.request(self, method, url, body, headers, encode_chunked) 1337 """Send a complete request to the server.""" -> 1338 self._send_request(method, url, body, headers, encode_chunked) File /usr/lib/python3.13/http/client.py:1384, in HTTPConnection._send_request(self, method, url, body, headers, encode_chunked) 1383 body = _encode(body, 'body') -> 1384 self.endheaders(body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1333, in HTTPConnection.endheaders(self, message_body, encode_chunked) 1332 raise CannotSendHeader() -> 1333 self._send_output(message_body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1093, in HTTPConnection._send_output(self, message_body, encode_chunked) 1092 del self._buffer[:] -> 1093 self.send(msg) 1095 if message_body is not None: 1096 1097 # create a consistent interface to message_body File /usr/lib/python3.13/http/client.py:1037, in HTTPConnection.send(self, data) 1036 if self.auto_open: -> 1037 self.connect() 1038 else: File /usr/lib/python3.13/http/client.py:1472, in HTTPSConnection.connect(self) 1470 "Connect to a host on a given (SSL) port." -> 1472 super().connect() 1474 if self._tunnel_host: File /usr/lib/python3.13/http/client.py:1003, in HTTPConnection.connect(self) 1002 sys.audit("http.client.connect", self, self.host, self.port) -> 1003 self.sock = self._create_connection( 1004 (self.host,self.port), self.timeout, self.source_address) 1005 # Might fail in OSs that don't implement TCP_NODELAY File /usr/lib/python3.13/socket.py:864, in create_connection(address, timeout, source_address, all_errors) 863 if not all_errors: --> 864 raise exceptions[0] 865 raise ExceptionGroup("create_connection failed", exceptions) File /usr/lib/python3.13/socket.py:849, in create_connection(address, timeout, source_address, all_errors) 848 sock.bind(source_address) --> 849 sock.connect(sa) 850 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused During handling of the above exception, another exception occurred: URLError Traceback (most recent call last) Cell In[3], line 6 3 from zipfile import ZipFile 5 # Download the dataset ----> 6 df = pd.read_table( 7 "https://raw.githubusercontent.com/jrnold/ssmodels-in-stan/master/StanStateSpace/data-raw/DK-data/internet.dat", 8 skiprows=1, header=None, sep='\s+', engine='python', 9 names=['internet','dinternet'] 10 ) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1405, in read_table(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend) 1392 kwds_defaults = _refine_defaults_read( 1393 dialect, 1394 delimiter, (...) 1401 dtype_backend=dtype_backend, 1402 ) 1403 kwds.update(kwds_defaults) -> 1405 return _read(filepath_or_buffer, kwds) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:620, in _read(filepath_or_buffer, kwds) 617 _validate_names(kwds.get("names", None)) 619 # Create the parser. --> 620 parser = TextFileReader(filepath_or_buffer, **kwds) 622 if chunksize or iterator: 623 return parser File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1620, in TextFileReader.__init__(self, f, engine, **kwds) 1617 self.options["has_index_names"] = kwds["has_index_names"] 1619 self.handles: IOHandles | None = None -> 1620 self._engine = self._make_engine(f, self.engine) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1880, in TextFileReader._make_engine(self, f, engine) 1878 if "b" not in mode: 1879 mode += "b" -> 1880 self.handles = get_handle( 1881 f, 1882 mode, 1883 encoding=self.options.get("encoding", None), 1884 compression=self.options.get("compression", None), 1885 memory_map=self.options.get("memory_map", False), 1886 is_text=is_text, 1887 errors=self.options.get("encoding_errors", "strict"), 1888 storage_options=self.options.get("storage_options", None), 1889 ) 1890 assert self.handles is not None 1891 f = self.handles.handle File /usr/lib/python3/dist-packages/pandas/io/common.py:728, in get_handle(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options) 725 codecs.lookup_error(errors) 727 # open URLs --> 728 ioargs = _get_filepath_or_buffer( 729 path_or_buf, 730 encoding=encoding, 731 compression=compression, 732 mode=mode, 733 storage_options=storage_options, 734 ) 736 handle = ioargs.filepath_or_buffer 737 handles: list[BaseBuffer] File /usr/lib/python3/dist-packages/pandas/io/common.py:384, in _get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode, storage_options) 382 # assuming storage_options is to be interpreted as headers 383 req_info = urllib.request.Request(filepath_or_buffer, headers=storage_options) --> 384 with urlopen(req_info) as req: 385 content_encoding = req.headers.get("Content-Encoding", None) 386 if content_encoding == "gzip": 387 # Override compression based on Content-Encoding header File /usr/lib/python3/dist-packages/pandas/io/common.py:289, in urlopen(*args, **kwargs) 283 """ 284 Lazy-import wrapper for stdlib urlopen, as that imports a big chunk of 285 the stdlib. 286 """ 287 import urllib.request --> 289 return urllib.request.urlopen(*args, **kwargs) File /usr/lib/python3.13/urllib/request.py:189, in urlopen(url, data, timeout, context) 187 else: 188 opener = _opener --> 189 return opener.open(url, data, timeout) File /usr/lib/python3.13/urllib/request.py:489, in OpenerDirector.open(self, fullurl, data, timeout) 486 req = meth(req) 488 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method()) --> 489 response = self._open(req, data) 491 # post-process response 492 meth_name = protocol+"_response" File /usr/lib/python3.13/urllib/request.py:506, in OpenerDirector._open(self, req, data) 503 return result 505 protocol = req.type --> 506 result = self._call_chain(self.handle_open, protocol, protocol + 507 '_open', req) 508 if result: 509 return result File /usr/lib/python3.13/urllib/request.py:466, in OpenerDirector._call_chain(self, chain, kind, meth_name, *args) 464 for handler in handlers: 465 func = getattr(handler, meth_name) --> 466 result = func(*args) 467 if result is not None: 468 return result File /usr/lib/python3.13/urllib/request.py:1367, in HTTPSHandler.https_open(self, req) 1366 def https_open(self, req): -> 1367 return self.do_open(http.client.HTTPSConnection, req, 1368 context=self._context) File /usr/lib/python3.13/urllib/request.py:1322, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error -> 1322 raise URLError(err) 1323 r = h.getresponse() 1324 except: URLError: ****************************************************************************** ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/ordinal_regression.ipynb An error occurred while executing the following cell: ------------------ url = "https://stats.idre.ucla.edu/stat/data/ologit.dta" data_student = pd.read_stata(url) ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3.13/urllib/request.py:1319, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1318 try: -> 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error File /usr/lib/python3.13/http/client.py:1338, in HTTPConnection.request(self, method, url, body, headers, encode_chunked) 1337 """Send a complete request to the server.""" -> 1338 self._send_request(method, url, body, headers, encode_chunked) File /usr/lib/python3.13/http/client.py:1384, in HTTPConnection._send_request(self, method, url, body, headers, encode_chunked) 1383 body = _encode(body, 'body') -> 1384 self.endheaders(body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1333, in HTTPConnection.endheaders(self, message_body, encode_chunked) 1332 raise CannotSendHeader() -> 1333 self._send_output(message_body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1093, in HTTPConnection._send_output(self, message_body, encode_chunked) 1092 del self._buffer[:] -> 1093 self.send(msg) 1095 if message_body is not None: 1096 1097 # create a consistent interface to message_body File /usr/lib/python3.13/http/client.py:1037, in HTTPConnection.send(self, data) 1036 if self.auto_open: -> 1037 self.connect() 1038 else: File /usr/lib/python3.13/http/client.py:1472, in HTTPSConnection.connect(self) 1470 "Connect to a host on a given (SSL) port." -> 1472 super().connect() 1474 if self._tunnel_host: File /usr/lib/python3.13/http/client.py:1003, in HTTPConnection.connect(self) 1002 sys.audit("http.client.connect", self, self.host, self.port) -> 1003 self.sock = self._create_connection( 1004 (self.host,self.port), self.timeout, self.source_address) 1005 # Might fail in OSs that don't implement TCP_NODELAY File /usr/lib/python3.13/socket.py:864, in create_connection(address, timeout, source_address, all_errors) 863 if not all_errors: --> 864 raise exceptions[0] 865 raise ExceptionGroup("create_connection failed", exceptions) File /usr/lib/python3.13/socket.py:849, in create_connection(address, timeout, source_address, all_errors) 848 sock.bind(source_address) --> 849 sock.connect(sa) 850 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused During handling of the above exception, another exception occurred: URLError Traceback (most recent call last) Cell In[2], line 2 1 url = "https://stats.idre.ucla.edu/stat/data/ologit.dta" ----> 2 data_student = pd.read_stata(url) File /usr/lib/python3/dist-packages/pandas/io/stata.py:2113, in read_stata(filepath_or_buffer, convert_dates, convert_categoricals, index_col, convert_missing, preserve_dtypes, columns, order_categoricals, chunksize, iterator, compression, storage_options) 2110 return reader 2112 with reader: -> 2113 return reader.read() File /usr/lib/python3/dist-packages/pandas/io/stata.py:1687, in StataReader.read(self, nrows, convert_dates, convert_categoricals, index_col, convert_missing, preserve_dtypes, columns, order_categoricals) 1675 @Appender(_read_method_doc) 1676 def read( 1677 self, (...) 1685 order_categoricals: bool | None = None, 1686 ) -> DataFrame: -> 1687 self._ensure_open() 1689 # Handle options 1690 if convert_dates is None: File /usr/lib/python3/dist-packages/pandas/io/stata.py:1179, in StataReader._ensure_open(self) 1175 """ 1176 Ensure the file has been opened and its header data read. 1177 """ 1178 if not hasattr(self, "_path_or_buf"): -> 1179 self._open_file() File /usr/lib/python3/dist-packages/pandas/io/stata.py:1192, in StataReader._open_file(self) 1185 if not self._entered: 1186 warnings.warn( 1187 "StataReader is being used without using a context manager. " 1188 "Using StataReader as a context manager is the only supported method.", 1189 ResourceWarning, 1190 stacklevel=find_stack_level(), 1191 ) -> 1192 handles = get_handle( 1193 self._original_path_or_buf, 1194 "rb", 1195 storage_options=self._storage_options, 1196 is_text=False, 1197 compression=self._compression, 1198 ) 1199 if hasattr(handles.handle, "seekable") and handles.handle.seekable(): 1200 # If the handle is directly seekable, use it without an extra copy. 1201 self._path_or_buf = handles.handle File /usr/lib/python3/dist-packages/pandas/io/common.py:728, in get_handle(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options) 725 codecs.lookup_error(errors) 727 # open URLs --> 728 ioargs = _get_filepath_or_buffer( 729 path_or_buf, 730 encoding=encoding, 731 compression=compression, 732 mode=mode, 733 storage_options=storage_options, 734 ) 736 handle = ioargs.filepath_or_buffer 737 handles: list[BaseBuffer] File /usr/lib/python3/dist-packages/pandas/io/common.py:384, in _get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode, storage_options) 382 # assuming storage_options is to be interpreted as headers 383 req_info = urllib.request.Request(filepath_or_buffer, headers=storage_options) --> 384 with urlopen(req_info) as req: 385 content_encoding = req.headers.get("Content-Encoding", None) 386 if content_encoding == "gzip": 387 # Override compression based on Content-Encoding header File /usr/lib/python3/dist-packages/pandas/io/common.py:289, in urlopen(*args, **kwargs) 283 """ 284 Lazy-import wrapper for stdlib urlopen, as that imports a big chunk of 285 the stdlib. 286 """ 287 import urllib.request --> 289 return urllib.request.urlopen(*args, **kwargs) File /usr/lib/python3.13/urllib/request.py:189, in urlopen(url, data, timeout, context) 187 else: 188 opener = _opener --> 189 return opener.open(url, data, timeout) File /usr/lib/python3.13/urllib/request.py:489, in OpenerDirector.open(self, fullurl, data, timeout) 486 req = meth(req) 488 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method()) --> 489 response = self._open(req, data) 491 # post-process response 492 meth_name = protocol+"_response" File /usr/lib/python3.13/urllib/request.py:506, in OpenerDirector._open(self, req, data) 503 return result 505 protocol = req.type --> 506 result = self._call_chain(self.handle_open, protocol, protocol + 507 '_open', req) 508 if result: 509 return result File /usr/lib/python3.13/urllib/request.py:466, in OpenerDirector._call_chain(self, chain, kind, meth_name, *args) 464 for handler in handlers: 465 func = getattr(handler, meth_name) --> 466 result = func(*args) 467 if result is not None: 468 return result File /usr/lib/python3.13/urllib/request.py:1367, in HTTPSHandler.https_open(self, req) 1366 def https_open(self, req): -> 1367 return self.do_open(http.client.HTTPSConnection, req, 1368 context=self._context) File /usr/lib/python3.13/urllib/request.py:1322, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error -> 1322 raise URLError(err) 1323 r = h.getresponse() 1324 except: URLError: An error occurred while executing the following cell: ------------------ url = "https://stats.idre.ucla.edu/stat/data/ologit.dta" data_student = pd.read_stata(url) ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3.13/urllib/request.py:1319, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1318 try: -> 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error File /usr/lib/python3.13/http/client.py:1338, in HTTPConnection.request(self, method, url, body, headers, encode_chunked) 1337 """Send a complete request to the server.""" -> 1338 self._send_request(method, url, body, headers, encode_chunked) File /usr/lib/python3.13/http/client.py:1384, in HTTPConnection._send_request(self, method, url, body, headers, encode_chunked) 1383 body = _encode(body, 'body') -> 1384 self.endheaders(body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1333, in HTTPConnection.endheaders(self, message_body, encode_chunked) 1332 raise CannotSendHeader() -> 1333 self._send_output(message_body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1093, in HTTPConnection._send_output(self, message_body, encode_chunked) 1092 del self._buffer[:] -> 1093 self.send(msg) 1095 if message_body is not None: 1096 1097 # create a consistent interface to message_body File /usr/lib/python3.13/http/client.py:1037, in HTTPConnection.send(self, data) 1036 if self.auto_open: -> 1037 self.connect() 1038 else: File /usr/lib/python3.13/http/client.py:1472, in HTTPSConnection.connect(self) 1470 "Connect to a host on a given (SSL) port." -> 1472 super().connect() 1474 if self._tunnel_host: File /usr/lib/python3.13/http/client.py:1003, in HTTPConnection.connect(self) 1002 sys.audit("http.client.connect", self, self.host, self.port) -> 1003 self.sock = self._create_connection( 1004 (self.host,self.port), self.timeout, self.source_address) 1005 # Might fail in OSs that don't implement TCP_NODELAY File /usr/lib/python3.13/socket.py:864, in create_connection(address, timeout, source_address, all_errors) 863 if not all_errors: --> 864 raise exceptions[0] 865 raise ExceptionGroup("create_connection failed", exceptions) File /usr/lib/python3.13/socket.py:849, in create_connection(address, timeout, source_address, all_errors) 848 sock.bind(source_address) --> 849 sock.connect(sa) 850 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused During handling of the above exception, another exception occurred: URLError Traceback (most recent call last) Cell In[2], line 2 1 url = "https://stats.idre.ucla.edu/stat/data/ologit.dta" ----> 2 data_student = pd.read_stata(url) File /usr/lib/python3/dist-packages/pandas/io/stata.py:2113, in read_stata(filepath_or_buffer, convert_dates, convert_categoricals, index_col, convert_missing, preserve_dtypes, columns, order_categoricals, chunksize, iterator, compression, storage_options) 2110 return reader 2112 with reader: -> 2113 return reader.read() File /usr/lib/python3/dist-packages/pandas/io/stata.py:1687, in StataReader.read(self, nrows, convert_dates, convert_categoricals, index_col, convert_missing, preserve_dtypes, columns, order_categoricals) 1675 @Appender(_read_method_doc) 1676 def read( 1677 self, (...) 1685 order_categoricals: bool | None = None, 1686 ) -> DataFrame: -> 1687 self._ensure_open() 1689 # Handle options 1690 if convert_dates is None: File /usr/lib/python3/dist-packages/pandas/io/stata.py:1179, in StataReader._ensure_open(self) 1175 """ 1176 Ensure the file has been opened and its header data read. 1177 """ 1178 if not hasattr(self, "_path_or_buf"): -> 1179 self._open_file() File /usr/lib/python3/dist-packages/pandas/io/stata.py:1192, in StataReader._open_file(self) 1185 if not self._entered: 1186 warnings.warn( 1187 "StataReader is being used without using a context manager. " 1188 "Using StataReader as a context manager is the only supported method.", 1189 ResourceWarning, 1190 stacklevel=find_stack_level(), 1191 ) -> 1192 handles = get_handle( 1193 self._original_path_or_buf, 1194 "rb", 1195 storage_options=self._storage_options, 1196 is_text=False, 1197 compression=self._compression, 1198 ) 1199 if hasattr(handles.handle, "seekable") and handles.handle.seekable(): 1200 # If the handle is directly seekable, use it without an extra copy. 1201 self._path_or_buf = handles.handle File /usr/lib/python3/dist-packages/pandas/io/common.py:728, in get_handle(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options) 725 codecs.lookup_error(errors) 727 # open URLs --> 728 ioargs = _get_filepath_or_buffer( 729 path_or_buf, 730 encoding=encoding, 731 compression=compression, 732 mode=mode, 733 storage_options=storage_options, 734 ) 736 handle = ioargs.filepath_or_buffer 737 handles: list[BaseBuffer] File /usr/lib/python3/dist-packages/pandas/io/common.py:384, in _get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode, storage_options) 382 # assuming storage_options is to be interpreted as headers 383 req_info = urllib.request.Request(filepath_or_buffer, headers=storage_options) --> 384 with urlopen(req_info) as req: 385 content_encoding = req.headers.get("Content-Encoding", None) 386 if content_encoding == "gzip": 387 # Override compression based on Content-Encoding header File /usr/lib/python3/dist-packages/pandas/io/common.py:289, in urlopen(*args, **kwargs) 283 """ 284 Lazy-import wrapper for stdlib urlopen, as that imports a big chunk of 285 the stdlib. 286 """ 287 import urllib.request --> 289 return urllib.request.urlopen(*args, **kwargs) File /usr/lib/python3.13/urllib/request.py:189, in urlopen(url, data, timeout, context) 187 else: 188 opener = _opener --> 189 return opener.open(url, data, timeout) File /usr/lib/python3.13/urllib/request.py:489, in OpenerDirector.open(self, fullurl, data, timeout) 486 req = meth(req) 488 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method()) --> 489 response = self._open(req, data) 491 # post-process response 492 meth_name = protocol+"_response" File /usr/lib/python3.13/urllib/request.py:506, in OpenerDirector._open(self, req, data) 503 return result 505 protocol = req.type --> 506 result = self._call_chain(self.handle_open, protocol, protocol + 507 '_open', req) 508 if result: 509 return result File /usr/lib/python3.13/urllib/request.py:466, in OpenerDirector._call_chain(self, chain, kind, meth_name, *args) 464 for handler in handlers: 465 func = getattr(handler, meth_name) --> 466 result = func(*args) 467 if result is not None: 468 return result File /usr/lib/python3.13/urllib/request.py:1367, in HTTPSHandler.https_open(self, req) 1366 def https_open(self, req): -> 1367 return self.do_open(http.client.HTTPSConnection, req, 1368 context=self._context) File /usr/lib/python3.13/urllib/request.py:1322, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error -> 1322 raise URLError(err) 1323 r = h.getresponse() 1324 except: URLError: ****************************************************************************** ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_sarimax_stata.ipynb An error occurred while executing the following cell: ------------------ # Dataset wpi1 = requests.get('https://www.stata-press.com/data/r12/wpi1.dta').content data = pd.read_stata(BytesIO(wpi1)) data.index = data.t # Set the frequency data.index.freq="QS-OCT" # Fit the model mod = sm.tsa.statespace.SARIMAX(data['wpi'], trend='c', order=(1,1,1)) res = mod.fit(disp=False) print(res.summary()) ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3/dist-packages/urllib3/connection.py:198, in HTTPConnection._new_conn(self) 197 try: --> 198 sock = connection.create_connection( 199 (self._dns_host, self.port), 200 self.timeout, 201 source_address=self.source_address, 202 socket_options=self.socket_options, 203 ) 204 except socket.gaierror as e: File /usr/lib/python3/dist-packages/urllib3/util/connection.py:85, in create_connection(address, timeout, source_address, socket_options) 84 try: ---> 85 raise err 86 finally: 87 # Break explicitly a reference cycle File /usr/lib/python3/dist-packages/urllib3/util/connection.py:73, in create_connection(address, timeout, source_address, socket_options) 72 sock.bind(source_address) ---> 73 sock.connect(sa) 74 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused The above exception was the direct cause of the following exception: NewConnectionError Traceback (most recent call last) File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:773, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw) 772 try: --> 773 self._prepare_proxy(conn) 774 except (BaseSSLError, OSError, SocketTimeout) as e: File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:1042, in HTTPSConnectionPool._prepare_proxy(self, conn) 1036 conn.set_tunnel( 1037 scheme=tunnel_scheme, 1038 host=self._tunnel_host, 1039 port=self.port, 1040 headers=self.proxy_headers, 1041 ) -> 1042 conn.connect() File /usr/lib/python3/dist-packages/urllib3/connection.py:753, in HTTPSConnection.connect(self) 752 sock: socket.socket | ssl.SSLSocket --> 753 self.sock = sock = self._new_conn() 754 server_hostname: str = self.host File /usr/lib/python3/dist-packages/urllib3/connection.py:213, in HTTPConnection._new_conn(self) 212 except OSError as e: --> 213 raise NewConnectionError( 214 self, f"Failed to establish a new connection: {e}" 215 ) from e 217 sys.audit("http.client.connect", self, self.host, self.port) NewConnectionError: : Failed to establish a new connection: [Errno 111] Connection refused The above exception was the direct cause of the following exception: ProxyError Traceback (most recent call last) ProxyError: ('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused')) The above exception was the direct cause of the following exception: MaxRetryError Traceback (most recent call last) File /usr/lib/python3/dist-packages/requests/adapters.py:644, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies) 643 try: --> 644 resp = conn.urlopen( 645 method=request.method, 646 url=url, 647 body=request.body, 648 headers=request.headers, 649 redirect=False, 650 assert_same_host=False, 651 preload_content=False, 652 decode_content=False, 653 retries=self.max_retries, 654 timeout=timeout, 655 chunked=chunked, 656 ) 658 except (ProtocolError, OSError) as err: File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:841, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw) 839 new_e = ProtocolError("Connection aborted.", new_e) --> 841 retries = retries.increment( 842 method, url, error=new_e, _pool=self, _stacktrace=sys.exc_info()[2] 843 ) 844 retries.sleep() File /usr/lib/python3/dist-packages/urllib3/util/retry.py:519, in Retry.increment(self, method, url, response, error, _pool, _stacktrace) 518 reason = error or ResponseError(cause) --> 519 raise MaxRetryError(_pool, url, reason) from reason # type: ignore[arg-type] 521 log.debug("Incremented Retry for (url='%s'): %r", url, new_retry) MaxRetryError: HTTPSConnectionPool(host='www.stata-press.com', port=443): Max retries exceeded with url: /data/r12/wpi1.dta (Caused by ProxyError('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused'))) During handling of the above exception, another exception occurred: ProxyError Traceback (most recent call last) Cell In[3], line 2 1 # Dataset ----> 2 wpi1 = requests.get('https://www.stata-press.com/data/r12/wpi1.dta').content 3 data = pd.read_stata(BytesIO(wpi1)) 4 data.index = data.t File /usr/lib/python3/dist-packages/requests/api.py:73, in get(url, params, **kwargs) 62 def get(url, params=None, **kwargs): 63 r"""Sends a GET request. 64 65 :param url: URL for the new :class:`Request` object. (...) 70 :rtype: requests.Response 71 """ ---> 73 return request("get", url, params=params, **kwargs) File /usr/lib/python3/dist-packages/requests/api.py:59, in request(method, url, **kwargs) 55 # By using the 'with' statement we are sure the session is closed, thus we 56 # avoid leaving sockets open which can trigger a ResourceWarning in some 57 # cases, and look like a memory leak in others. 58 with sessions.Session() as session: ---> 59 return session.request(method=method, url=url, **kwargs) File /usr/lib/python3/dist-packages/requests/sessions.py:589, in Session.request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json) 584 send_kwargs = { 585 "timeout": timeout, 586 "allow_redirects": allow_redirects, 587 } 588 send_kwargs.update(settings) --> 589 resp = self.send(prep, **send_kwargs) 591 return resp File /usr/lib/python3/dist-packages/requests/sessions.py:703, in Session.send(self, request, **kwargs) 700 start = preferred_clock() 702 # Send the request --> 703 r = adapter.send(request, **kwargs) 705 # Total elapsed time of the request (approximately) 706 elapsed = preferred_clock() - start File /usr/lib/python3/dist-packages/requests/adapters.py:671, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies) 668 raise RetryError(e, request=request) 670 if isinstance(e.reason, _ProxyError): --> 671 raise ProxyError(e, request=request) 673 if isinstance(e.reason, _SSLError): 674 # This branch is for urllib3 v1.22 and later. 675 raise SSLError(e, request=request) ProxyError: HTTPSConnectionPool(host='www.stata-press.com', port=443): Max retries exceeded with url: /data/r12/wpi1.dta (Caused by ProxyError('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused'))) An error occurred while executing the following cell: ------------------ # Dataset wpi1 = requests.get('https://www.stata-press.com/data/r12/wpi1.dta').content data = pd.read_stata(BytesIO(wpi1)) data.index = data.t # Set the frequency data.index.freq="QS-OCT" # Fit the model mod = sm.tsa.statespace.SARIMAX(data['wpi'], trend='c', order=(1,1,1)) res = mod.fit(disp=False) print(res.summary()) ------------------ --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3/dist-packages/urllib3/connection.py:198, in HTTPConnection._new_conn(self) 197 try: --> 198 sock = connection.create_connection( 199 (self._dns_host, self.port), 200 self.timeout, 201 source_address=self.source_address, 202 socket_options=self.socket_options, 203 ) 204 except socket.gaierror as e: File /usr/lib/python3/dist-packages/urllib3/util/connection.py:85, in create_connection(address, timeout, source_address, socket_options) 84 try: ---> 85 raise err 86 finally: 87 # Break explicitly a reference cycle File /usr/lib/python3/dist-packages/urllib3/util/connection.py:73, in create_connection(address, timeout, source_address, socket_options) 72 sock.bind(source_address) ---> 73 sock.connect(sa) 74 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused The above exception was the direct cause of the following exception: NewConnectionError Traceback (most recent call last) File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:773, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw) 772 try: --> 773 self._prepare_proxy(conn) 774 except (BaseSSLError, OSError, SocketTimeout) as e: File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:1042, in HTTPSConnectionPool._prepare_proxy(self, conn) 1036 conn.set_tunnel( 1037 scheme=tunnel_scheme, 1038 host=self._tunnel_host, 1039 port=self.port, 1040 headers=self.proxy_headers, 1041 ) -> 1042 conn.connect() File /usr/lib/python3/dist-packages/urllib3/connection.py:753, in HTTPSConnection.connect(self) 752 sock: socket.socket | ssl.SSLSocket --> 753 self.sock = sock = self._new_conn() 754 server_hostname: str = self.host File /usr/lib/python3/dist-packages/urllib3/connection.py:213, in HTTPConnection._new_conn(self) 212 except OSError as e: --> 213 raise NewConnectionError( 214 self, f"Failed to establish a new connection: {e}" 215 ) from e 217 sys.audit("http.client.connect", self, self.host, self.port) NewConnectionError: : Failed to establish a new connection: [Errno 111] Connection refused The above exception was the direct cause of the following exception: ProxyError Traceback (most recent call last) ProxyError: ('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused')) The above exception was the direct cause of the following exception: MaxRetryError Traceback (most recent call last) File /usr/lib/python3/dist-packages/requests/adapters.py:644, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies) 643 try: --> 644 resp = conn.urlopen( 645 method=request.method, 646 url=url, 647 body=request.body, 648 headers=request.headers, 649 redirect=False, 650 assert_same_host=False, 651 preload_content=False, 652 decode_content=False, 653 retries=self.max_retries, 654 timeout=timeout, 655 chunked=chunked, 656 ) 658 except (ProtocolError, OSError) as err: File /usr/lib/python3/dist-packages/urllib3/connectionpool.py:841, in HTTPConnectionPool.urlopen(self, method, url, body, headers, retries, redirect, assert_same_host, timeout, pool_timeout, release_conn, chunked, body_pos, preload_content, decode_content, **response_kw) 839 new_e = ProtocolError("Connection aborted.", new_e) --> 841 retries = retries.increment( 842 method, url, error=new_e, _pool=self, _stacktrace=sys.exc_info()[2] 843 ) 844 retries.sleep() File /usr/lib/python3/dist-packages/urllib3/util/retry.py:519, in Retry.increment(self, method, url, response, error, _pool, _stacktrace) 518 reason = error or ResponseError(cause) --> 519 raise MaxRetryError(_pool, url, reason) from reason # type: ignore[arg-type] 521 log.debug("Incremented Retry for (url='%s'): %r", url, new_retry) MaxRetryError: HTTPSConnectionPool(host='www.stata-press.com', port=443): Max retries exceeded with url: /data/r12/wpi1.dta (Caused by ProxyError('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused'))) During handling of the above exception, another exception occurred: ProxyError Traceback (most recent call last) Cell In[3], line 2 1 # Dataset ----> 2 wpi1 = requests.get('https://www.stata-press.com/data/r12/wpi1.dta').content 3 data = pd.read_stata(BytesIO(wpi1)) 4 data.index = data.t File /usr/lib/python3/dist-packages/requests/api.py:73, in get(url, params, **kwargs) 62 def get(url, params=None, **kwargs): 63 r"""Sends a GET request. 64 65 :param url: URL for the new :class:`Request` object. (...) 70 :rtype: requests.Response 71 """ ---> 73 return request("get", url, params=params, **kwargs) File /usr/lib/python3/dist-packages/requests/api.py:59, in request(method, url, **kwargs) 55 # By using the 'with' statement we are sure the session is closed, thus we 56 # avoid leaving sockets open which can trigger a ResourceWarning in some 57 # cases, and look like a memory leak in others. 58 with sessions.Session() as session: ---> 59 return session.request(method=method, url=url, **kwargs) File /usr/lib/python3/dist-packages/requests/sessions.py:589, in Session.request(self, method, url, params, data, headers, cookies, files, auth, timeout, allow_redirects, proxies, hooks, stream, verify, cert, json) 584 send_kwargs = { 585 "timeout": timeout, 586 "allow_redirects": allow_redirects, 587 } 588 send_kwargs.update(settings) --> 589 resp = self.send(prep, **send_kwargs) 591 return resp File /usr/lib/python3/dist-packages/requests/sessions.py:703, in Session.send(self, request, **kwargs) 700 start = preferred_clock() 702 # Send the request --> 703 r = adapter.send(request, **kwargs) 705 # Total elapsed time of the request (approximately) 706 elapsed = preferred_clock() - start File /usr/lib/python3/dist-packages/requests/adapters.py:671, in HTTPAdapter.send(self, request, stream, timeout, verify, cert, proxies) 668 raise RetryError(e, request=request) 670 if isinstance(e.reason, _ProxyError): --> 671 raise ProxyError(e, request=request) 673 if isinstance(e.reason, _SSLError): 674 # This branch is for urllib3 v1.22 and later. 675 raise SSLError(e, request=request) ProxyError: HTTPSConnectionPool(host='www.stata-press.com', port=443): Max retries exceeded with url: /data/r12/wpi1.dta (Caused by ProxyError('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused'))) ****************************************************************************** ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/theta-model.ipynb An error occurred while executing the following cell: ------------------ import matplotlib.pyplot as plt import numpy as np import pandas as pd import pandas_datareader as pdr import seaborn as sns plt.rc("figure", figsize=(16, 8)) plt.rc("font", size=15) plt.rc("lines", linewidth=3) sns.set_style("darkgrid") ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 4 2 import numpy as np 3 import pandas as pd ----> 4 import pandas_datareader as pdr 5 import seaborn as sns 7 plt.rc("figure", figsize=(16, 8)) ModuleNotFoundError: No module named 'pandas_datareader' An error occurred while executing the following cell: ------------------ import matplotlib.pyplot as plt import numpy as np import pandas as pd import pandas_datareader as pdr import seaborn as sns plt.rc("figure", figsize=(16, 8)) plt.rc("font", size=15) plt.rc("lines", linewidth=3) sns.set_style("darkgrid") ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 4 2 import numpy as np 3 import pandas as pd ----> 4 import pandas_datareader as pdr 5 import seaborn as sns 7 plt.rc("figure", figsize=(16, 8)) ModuleNotFoundError: No module named 'pandas_datareader' ****************************************************************************** ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/rolling_ls.ipynb An error occurred while executing the following cell: ------------------ import matplotlib.pyplot as plt import numpy as np import pandas as pd import pandas_datareader as pdr import seaborn import statsmodels.api as sm from statsmodels.regression.rolling import RollingOLS seaborn.set_style("darkgrid") pd.plotting.register_matplotlib_converters() %matplotlib inline ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 4 2 import numpy as np 3 import pandas as pd ----> 4 import pandas_datareader as pdr 5 import seaborn 7 import statsmodels.api as sm ModuleNotFoundError: No module named 'pandas_datareader' An error occurred while executing the following cell: ------------------ import matplotlib.pyplot as plt import numpy as np import pandas as pd import pandas_datareader as pdr import seaborn import statsmodels.api as sm from statsmodels.regression.rolling import RollingOLS seaborn.set_style("darkgrid") pd.plotting.register_matplotlib_converters() %matplotlib inline ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[1], line 4 2 import numpy as np 3 import pandas as pd ----> 4 import pandas_datareader as pdr 5 import seaborn 7 import statsmodels.api as sm ModuleNotFoundError: No module named 'pandas_datareader' ****************************************************************************** Exception ignored in atexit callback >: Traceback (most recent call last): File "/usr/lib/python3/dist-packages/ipykernel/kernelapp.py", line 422, in close self.context.term() File "/usr/lib/python3/dist-packages/zmq/sugar/context.py", line 264, in term super().term() File "_zmq.py", line 586, in zmq.backend.cython._zmq.Context.term File "_zmq.py", line 169, in zmq.backend.cython._zmq._check_rc KeyboardInterrupt: ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_sarimax_faq.ipynb Kernel didn't respond in 60 seconds Kernel didn't respond in 60 seconds ****************************************************************************** Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_sarimax_faq.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/distributed_estimation.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/regression_diagnostics.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_arma_0.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/wls.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_concentrated_scale.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/tsa_arma_0.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_fixed_params.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/plots_boxplots.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/mixed_lm_example.ipynb ****************************************************************************** ERROR: Error occurred when running /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_tvpvar_mcmc_cfa.ipynb An error occurred while executing the following cell: ------------------ import arviz as az # Collect the observation error covariance parameters az_obs_cov = az.convert_to_inference_data({ ('Var[%s]' % mod.endog_names[i] if i == j else 'Cov[%s, %s]' % (mod.endog_names[i], mod.endog_names[j])): store_obs_cov[nburn + 1:, i, j] for i in range(mod.k_endog) for j in range(i, mod.k_endog)}) # Plot the credible intervals az.plot_forest(az_obs_cov, figsize=(8, 7)); ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[16], line 1 ----> 1 import arviz as az 3 # Collect the observation error covariance parameters 4 az_obs_cov = az.convert_to_inference_data({ 5 ('Var[%s]' % mod.endog_names[i] if i == j else 6 'Cov[%s, %s]' % (mod.endog_names[i], mod.endog_names[j])): 7 store_obs_cov[nburn + 1:, i, j] 8 for i in range(mod.k_endog) for j in range(i, mod.k_endog)}) ModuleNotFoundError: No module named 'arviz' An error occurred while executing the following cell: ------------------ import arviz as az # Collect the observation error covariance parameters az_obs_cov = az.convert_to_inference_data({ ('Var[%s]' % mod.endog_names[i] if i == j else 'Cov[%s, %s]' % (mod.endog_names[i], mod.endog_names[j])): store_obs_cov[nburn + 1:, i, j] for i in range(mod.k_endog) for j in range(i, mod.k_endog)}) # Plot the credible intervals az.plot_forest(az_obs_cov, figsize=(8, 7)); ------------------ --------------------------------------------------------------------------- ModuleNotFoundError Traceback (most recent call last) Cell In[16], line 1 ----> 1 import arviz as az 3 # Collect the observation error covariance parameters 4 az_obs_cov = az.convert_to_inference_data({ 5 ('Var[%s]' % mod.endog_names[i] if i == j else 6 'Cov[%s, %s]' % (mod.endog_names[i], mod.endog_names[j])): 7 store_obs_cov[nburn + 1:, i, j] 8 for i in range(mod.k_endog) for j in range(i, mod.k_endog)}) ModuleNotFoundError: No module named 'arviz' ****************************************************************************** Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_tvpvar_mcmc_cfa.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_varmax.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_news.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/postestimation_poisson.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_dfm_coincident.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/autoregressions.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/treatment_effect.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/lowess.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/chi2_fitting.ipynb Finished 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/build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/ordinal_regression.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/metaanalysis1.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/regression_plots.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/tsa_dates.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/theta-model.ipynb Finished /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/rolling_ls.ipynb Copying (without executing) /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_custom_models.ipynb to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/statespace_custom_models.ipynb Finished (without execution) /build/reproducible-path/statsmodels-0.14.5+dfsg/examples/notebooks/statespace_custom_models.ipynb Copying notebooks that failed execution (there are usually several in Debian because some need network and/or dependencies we don't have) cp -nav ../examples/notebooks/*.ipynb -t source/examples/notebooks/generated || true '../examples/notebooks/autoregressions.ipynb' -> 'source/examples/notebooks/generated/autoregressions.ipynb' '../examples/notebooks/autoregressive_distributed_lag.ipynb' -> 'source/examples/notebooks/generated/autoregressive_distributed_lag.ipynb' '../examples/notebooks/contrasts.ipynb' -> 'source/examples/notebooks/generated/contrasts.ipynb' '../examples/notebooks/interactions_anova.ipynb' -> 'source/examples/notebooks/generated/interactions_anova.ipynb' '../examples/notebooks/linear_regression_diagnostics_plots.ipynb' -> 'source/examples/notebooks/generated/linear_regression_diagnostics_plots.ipynb' '../examples/notebooks/markov_autoregression.ipynb' -> 'source/examples/notebooks/generated/markov_autoregression.ipynb' '../examples/notebooks/mstl_decomposition.ipynb' -> 'source/examples/notebooks/generated/mstl_decomposition.ipynb' '../examples/notebooks/ordinal_regression.ipynb' -> 'source/examples/notebooks/generated/ordinal_regression.ipynb' '../examples/notebooks/recursive_ls.ipynb' -> 'source/examples/notebooks/generated/recursive_ls.ipynb' '../examples/notebooks/rolling_ls.ipynb' -> 'source/examples/notebooks/generated/rolling_ls.ipynb' '../examples/notebooks/statespace_chandrasekhar.ipynb' -> 'source/examples/notebooks/generated/statespace_chandrasekhar.ipynb' '../examples/notebooks/statespace_cycles.ipynb' -> 'source/examples/notebooks/generated/statespace_cycles.ipynb' '../examples/notebooks/statespace_dfm_coincident.ipynb' -> 'source/examples/notebooks/generated/statespace_dfm_coincident.ipynb' '../examples/notebooks/statespace_fixed_params.ipynb' -> 'source/examples/notebooks/generated/statespace_fixed_params.ipynb' '../examples/notebooks/statespace_local_linear_trend.ipynb' -> 'source/examples/notebooks/generated/statespace_local_linear_trend.ipynb' '../examples/notebooks/statespace_news.ipynb' -> 'source/examples/notebooks/generated/statespace_news.ipynb' '../examples/notebooks/statespace_sarimax_faq.ipynb' -> 'source/examples/notebooks/generated/statespace_sarimax_faq.ipynb' '../examples/notebooks/statespace_sarimax_internet.ipynb' -> 'source/examples/notebooks/generated/statespace_sarimax_internet.ipynb' '../examples/notebooks/statespace_sarimax_pymc3.ipynb' -> 'source/examples/notebooks/generated/statespace_sarimax_pymc3.ipynb' '../examples/notebooks/statespace_sarimax_stata.ipynb' -> 'source/examples/notebooks/generated/statespace_sarimax_stata.ipynb' '../examples/notebooks/statespace_structural_harvey_jaeger.ipynb' -> 'source/examples/notebooks/generated/statespace_structural_harvey_jaeger.ipynb' '../examples/notebooks/statespace_tvpvar_mcmc_cfa.ipynb' -> 'source/examples/notebooks/generated/statespace_tvpvar_mcmc_cfa.ipynb' '../examples/notebooks/statespace_varmax.ipynb' -> 'source/examples/notebooks/generated/statespace_varmax.ipynb' '../examples/notebooks/theta-model.ipynb' -> 'source/examples/notebooks/generated/theta-model.ipynb' Replacing timestamps and build paths in examples output for reproducibility for html in `find source/examples/notebooks/generated -name "*.html" -o -name "*.ipynb" -o -name "*.ipynb.txt"` ; do \ sed -i -e 's#/build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/#/usr/lib/python3/dist-packages/statsmodels/#g' \ -e 's# at 0x[0-9a-f]\{8,16\}\(>\|>\)# at 0xadde5de1e8ed\1#g' \ -e 's#tmp/ipykernel_[0-9]\+#tmp/ipykernel_nnnnnnn#g' \ -e 's#^\s\+.\(iopub.execute_input\|iopub.status.busy\|iopub.status.idle\|shell.execute_reply\).:.*# #g' \ -e 's#\(Date:.*\)[A-Z][a-z]\+, \+[0-9]\+,\? \+[A-Z][a-z]\+,\? \+[0-9]\+#\1Sun, 10 Aug 2025#g' \ -e 's#\(Time:.*\)[0-9][0-9]:[0-9][0-9]:[0-9][0-9]#\113:13:47#g' ${html} ; \ done Running sphinx-build @sphinx-build -M html source build Running Sphinx v8.2.3 loading translations [en]... done Converting `source_suffix = '.rst'` to `source_suffix = {'.rst': 'restructuredtext'}`. loading intersphinx inventory 'numpy' from /usr/share/doc/python-numpy/html/objects.inv ... loading intersphinx inventory 'python' from /usr/share/doc/python3-doc/html/objects.inv ... loading intersphinx inventory 'pydagogue' from https://matthew-brett.github.io/pydagogue/objects.inv ... loading intersphinx inventory 'matplotlib' from /usr/share/doc/python-matplotlib-doc/html/objects.inv ... loading intersphinx inventory 'scipy' from /usr/share/doc/python-scipy-doc/html/objects.inv ... loading intersphinx inventory 'pandas' from /usr/share/doc/python-pandas-doc/html/objects.inv ... WARNING: failed to reach any of the inventories with the following issues: intersphinx inventory 'https://matthew-brett.github.io/pydagogue/objects.inv' not fetchable due to : HTTPSConnectionPool(host='matthew-brett.github.io', port=443): Max retries exceeded with url: /pydagogue/objects.inv (Caused by ProxyError('Unable to connect to proxy', NewConnectionError(': Failed to establish a new connection: [Errno 111] Connection refused'))) Writing evaluated template result to /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/build/html/_static/nbsphinx-code-cells.css [autosummary] generating autosummary for: about.rst, anova.rst, api-structure.rst, api.rst, contingency_tables.rst, contrasts.rst, datasets/generated/anes96.rst, datasets/generated/cancer.rst, datasets/generated/ccard.rst, datasets/generated/china_smoking.rst, ..., rlm.rst, rlm_techn1.rst, sandbox.rst, statespace.rst, stats.rst, tools.rst, treatment.rst, tsa.rst, user-guide.rst, vector_ar.rst [autosummary] generating autosummary for: /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/datasets/statsmodels.datasets.clear_data_home.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/datasets/statsmodels.datasets.get_data_home.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/datasets/statsmodels.datasets.get_rdataset.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/datasets/statsmodels.datasets.webuse.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/dev/generated/statsmodels.__init__.test.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/dev/generated/statsmodels.base.model.GenericLikelihoodModel.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/dev/generated/statsmodels.base.model.GenericLikelihoodModelResults.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/dev/generated/statsmodels.base.model.LikelihoodModel.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/dev/generated/statsmodels.base.model.LikelihoodModelResults.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/dev/generated/statsmodels.base.model.Model.rst, ..., /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.var_model.VARResults.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.vecm.CointRankResults.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.vecm.JohansenTestResult.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.vecm.VECM.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.vecm.VECMResults.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.vecm.coint_johansen.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.vecm.select_coint_rank.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.vecm.select_order.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.x13.x13_arima_analysis.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.x13.x13_arima_select_order.rst [autosummary] generating autosummary for: /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/dev/generated/statsmodels.base.model.GenericLikelihoodModel.endog_names.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/dev/generated/statsmodels.base.model.GenericLikelihoodModel.exog_names.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/dev/generated/statsmodels.base.model.GenericLikelihoodModel.expandparams.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/dev/generated/statsmodels.base.model.GenericLikelihoodModel.fit.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/dev/generated/statsmodels.base.model.GenericLikelihoodModel.from_formula.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/dev/generated/statsmodels.base.model.GenericLikelihoodModel.hessian.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/dev/generated/statsmodels.base.model.GenericLikelihoodModel.hessian_factor.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/dev/generated/statsmodels.base.model.GenericLikelihoodModel.information.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/dev/generated/statsmodels.base.model.GenericLikelihoodModel.initialize.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/dev/generated/statsmodels.base.model.GenericLikelihoodModel.loglike.rst, ..., /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.vecm.VECMResults.test_granger_causality.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.vecm.VECMResults.test_inst_causality.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.vecm.VECMResults.test_normality.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.vecm.VECMResults.test_whiteness.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.vecm.VECMResults.tvalues_alpha.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.vecm.VECMResults.tvalues_beta.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.vecm.VECMResults.tvalues_det_coef.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.vecm.VECMResults.tvalues_det_coef_coint.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.vecm.VECMResults.tvalues_gamma.rst, /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.vecm.VECMResults.var_rep.rst building [mo]: targets for 0 po files that are out of date writing output... building [html]: targets for 187 source files that are out of date updating environment: [new config] 6467 added, 0 changed, 0 removed reading sources... [ 0%] about reading sources... [ 0%] anova reading sources... [ 0%] api reading sources... [ 0%] api-structure reading sources... [ 0%] contingency_tables reading sources... [ 0%] contrasts reading sources... [ 0%] datasets/generated/anes96 reading sources... [ 0%] datasets/generated/cancer reading sources... [ 0%] datasets/generated/ccard reading sources... [ 0%] datasets/generated/china_smoking reading sources... [ 0%] datasets/generated/co2 reading sources... [ 0%] datasets/generated/committee reading sources... [ 0%] datasets/generated/copper reading sources... [ 0%] datasets/generated/cpunish reading sources... [ 0%] datasets/generated/danish_data reading sources... [ 0%] datasets/generated/elnino reading sources... [ 0%] datasets/generated/engel reading sources... [ 0%] datasets/generated/fair reading sources... [ 0%] datasets/generated/fertility reading sources... [ 0%] datasets/generated/grunfeld reading sources... [ 0%] datasets/generated/heart reading sources... 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Replace 'statsmodels.tools.print_version.show_versions' with 'tools.print_version.show_versions'. [autosummary.import_cycle] /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/anova.rst:6: WARNING: Duplicate explicit target name: "anova". [docutils] WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 50 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3.13/urllib/request.py:1319, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1318 try: -> 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error File /usr/lib/python3.13/http/client.py:1338, in HTTPConnection.request(self, method, url, body, headers, encode_chunked) 1337 """Send a complete request to the server.""" -> 1338 self._send_request(method, url, body, headers, encode_chunked) File /usr/lib/python3.13/http/client.py:1384, in HTTPConnection._send_request(self, method, url, body, headers, encode_chunked) 1383 body = _encode(body, 'body') -> 1384 self.endheaders(body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1333, in HTTPConnection.endheaders(self, message_body, encode_chunked) 1332 raise CannotSendHeader() -> 1333 self._send_output(message_body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1093, in HTTPConnection._send_output(self, message_body, encode_chunked) 1092 del self._buffer[:] -> 1093 self.send(msg) 1095 if message_body is not None: 1096 1097 # create a consistent interface to message_body File /usr/lib/python3.13/http/client.py:1037, in HTTPConnection.send(self, data) 1036 if self.auto_open: -> 1037 self.connect() 1038 else: File /usr/lib/python3.13/http/client.py:1472, in HTTPSConnection.connect(self) 1470 "Connect to a host on a given (SSL) port." -> 1472 super().connect() 1474 if self._tunnel_host: File /usr/lib/python3.13/http/client.py:1003, in HTTPConnection.connect(self) 1002 sys.audit("http.client.connect", self, self.host, self.port) -> 1003 self.sock = self._create_connection( 1004 (self.host,self.port), self.timeout, self.source_address) 1005 # Might fail in OSs that don't implement TCP_NODELAY File /usr/lib/python3.13/socket.py:864, in create_connection(address, timeout, source_address, all_errors) 863 if not all_errors: --> 864 raise exceptions[0] 865 raise ExceptionGroup("create_connection failed", exceptions) File /usr/lib/python3.13/socket.py:849, in create_connection(address, timeout, source_address, all_errors) 848 sock.bind(source_address) --> 849 sock.connect(sa) 850 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused During handling of the above exception, another exception occurred: URLError Traceback (most recent call last) Cell In[3], line 1 ----> 1 hsb2 = pandas.read_csv(url) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1026, in read_csv(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, date_format, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, encoding_errors, dialect, on_bad_lines, delim_whitespace, low_memory, memory_map, float_precision, storage_options, dtype_backend) 1013 kwds_defaults = _refine_defaults_read( 1014 dialect, 1015 delimiter, (...) 1022 dtype_backend=dtype_backend, 1023 ) 1024 kwds.update(kwds_defaults) -> 1026 return _read(filepath_or_buffer, kwds) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:620, in _read(filepath_or_buffer, kwds) 617 _validate_names(kwds.get("names", None)) 619 # Create the parser. --> 620 parser = TextFileReader(filepath_or_buffer, **kwds) 622 if chunksize or iterator: 623 return parser File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1620, in TextFileReader.__init__(self, f, engine, **kwds) 1617 self.options["has_index_names"] = kwds["has_index_names"] 1619 self.handles: IOHandles | None = None -> 1620 self._engine = self._make_engine(f, self.engine) File /usr/lib/python3/dist-packages/pandas/io/parsers/readers.py:1880, in TextFileReader._make_engine(self, f, engine) 1878 if "b" not in mode: 1879 mode += "b" -> 1880 self.handles = get_handle( 1881 f, 1882 mode, 1883 encoding=self.options.get("encoding", None), 1884 compression=self.options.get("compression", None), 1885 memory_map=self.options.get("memory_map", False), 1886 is_text=is_text, 1887 errors=self.options.get("encoding_errors", "strict"), 1888 storage_options=self.options.get("storage_options", None), 1889 ) 1890 assert self.handles is not None 1891 f = self.handles.handle File /usr/lib/python3/dist-packages/pandas/io/common.py:728, in get_handle(path_or_buf, mode, encoding, compression, memory_map, is_text, errors, storage_options) 725 codecs.lookup_error(errors) 727 # open URLs --> 728 ioargs = _get_filepath_or_buffer( 729 path_or_buf, 730 encoding=encoding, 731 compression=compression, 732 mode=mode, 733 storage_options=storage_options, 734 ) 736 handle = ioargs.filepath_or_buffer 737 handles: list[BaseBuffer] File /usr/lib/python3/dist-packages/pandas/io/common.py:384, in _get_filepath_or_buffer(filepath_or_buffer, encoding, compression, mode, storage_options) 382 # assuming storage_options is to be interpreted as headers 383 req_info = urllib.request.Request(filepath_or_buffer, headers=storage_options) --> 384 with urlopen(req_info) as req: 385 content_encoding = req.headers.get("Content-Encoding", None) 386 if content_encoding == "gzip": 387 # Override compression based on Content-Encoding header File /usr/lib/python3/dist-packages/pandas/io/common.py:289, in urlopen(*args, **kwargs) 283 """ 284 Lazy-import wrapper for stdlib urlopen, as that imports a big chunk of 285 the stdlib. 286 """ 287 import urllib.request --> 289 return urllib.request.urlopen(*args, **kwargs) File /usr/lib/python3.13/urllib/request.py:189, in urlopen(url, data, timeout, context) 187 else: 188 opener = _opener --> 189 return opener.open(url, data, timeout) File /usr/lib/python3.13/urllib/request.py:489, in OpenerDirector.open(self, fullurl, data, timeout) 486 req = meth(req) 488 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method()) --> 489 response = self._open(req, data) 491 # post-process response 492 meth_name = protocol+"_response" File /usr/lib/python3.13/urllib/request.py:506, in OpenerDirector._open(self, req, data) 503 return result 505 protocol = req.type --> 506 result = self._call_chain(self.handle_open, protocol, protocol + 507 '_open', req) 508 if result: 509 return result File /usr/lib/python3.13/urllib/request.py:466, in OpenerDirector._call_chain(self, chain, kind, meth_name, *args) 464 for handler in handlers: 465 func = getattr(handler, meth_name) --> 466 result = func(*args) 467 if result is not None: 468 return result File /usr/lib/python3.13/urllib/request.py:1367, in HTTPSHandler.https_open(self, req) 1366 def https_open(self, req): -> 1367 return self.do_open(http.client.HTTPSConnection, req, 1368 context=self._context) File /usr/lib/python3.13/urllib/request.py:1322, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error -> 1322 raise URLError(err) 1323 r = h.getresponse() 1324 except: URLError: <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 56 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[4], line 1 ----> 1 hsb2.groupby('race')['write'].mean() NameError: name 'hsb2' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 74 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[9], line 1 ----> 1 contrast.matrix[hsb2.race-1, :][:20] NameError: name 'hsb2' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 83 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[11], line 1 ----> 1 mod = ols("write ~ C(race, Treatment)", data=hsb2) NameError: name 'hsb2' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 83 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[12], line 1 ----> 1 res = mod.fit() NameError: name 'mod' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 83 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[13], line 1 ----> 1 print(res.summary()) NameError: name 'res' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 100 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[16], line 1 ----> 1 mod = ols("write ~ C(race, Simple)", data=hsb2) NameError: name 'hsb2' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 100 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[17], line 1 ----> 1 res = mod.fit() NameError: name 'mod' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 100 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[18], line 1 ----> 1 print(res.summary()) NameError: name 'res' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 115 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[22], line 1 ----> 1 mod = ols("write ~ C(race, Sum)", data=hsb2) NameError: name 'hsb2' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 115 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[23], line 1 ----> 1 res = mod.fit() NameError: name 'mod' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 115 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[24], line 1 ----> 1 print(res.summary()) NameError: name 'res' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 121 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[25], line 1 ----> 1 hsb2.groupby('race')['write'].mean().mean() NameError: name 'hsb2' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 136 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[29], line 1 ----> 1 mod = ols("write ~ C(race, Diff)", data=hsb2) NameError: name 'hsb2' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 136 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[30], line 1 ----> 1 res = mod.fit() NameError: name 'mod' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 136 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[31], line 1 ----> 1 print(res.summary()) NameError: name 'res' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 144 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[32], line 1 ----> 1 res.params["C(race, Diff)[D.1]"] NameError: name 'res' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 144 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[33], line 1 ----> 1 hsb2.groupby('race').mean()["write"].loc[2] - \ 2 hsb2.groupby('race').mean()["write"].loc[1] NameError: name 'hsb2' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 159 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[37], line 1 ----> 1 mod = ols("write ~ C(race, Helmert)", data=hsb2) NameError: name 'hsb2' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 159 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[38], line 1 ----> 1 res = mod.fit() NameError: name 'mod' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 159 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[39], line 1 ----> 1 print(res.summary()) NameError: name 'res' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 166 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[40], line 1 ----> 1 grouped = hsb2.groupby('race') NameError: name 'hsb2' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 166 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[41], line 1 ----> 1 grouped.mean()["write"].loc[4] - grouped.mean()["write"].loc[:3].mean() NameError: name 'grouped' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 176 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[43], line 1 ----> 1 1./k * (grouped.mean()["write"].loc[k] - grouped.mean()["write"].loc[:k-1].mean()) NameError: name 'grouped' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 176 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[45], line 1 ----> 1 1./k * (grouped.mean()["write"].loc[k] - grouped.mean()["write"].loc[:k-1].mean()) NameError: name 'grouped' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 191 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[46], line 1 ----> 1 _, bins = np.histogram(hsb2.read, 3) NameError: name 'hsb2' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 191 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[47], line 2 1 try: # requires numpy main ----> 2 readcat = np.digitize(hsb2.read, bins, True) 3 except: NameError: name 'hsb2' is not defined During handling of the above exception, another exception occurred: NameError Traceback (most recent call last) Cell In[47], line 4 2 readcat = np.digitize(hsb2.read, bins, True) 3 except: ----> 4 readcat = np.digitize(hsb2.read, bins) NameError: name 'hsb2' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 191 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[48], line 1 ----> 1 hsb2['readcat'] = readcat NameError: name 'readcat' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 191 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[49], line 1 ----> 1 hsb2.groupby('readcat').mean()['write'] NameError: name 'hsb2' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 202 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[51], line 1 ----> 1 levels = hsb2.readcat.unique().tolist() NameError: name 'hsb2' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 202 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[54], line 1 ----> 1 mod = ols("write ~ C(readcat, Poly)", data=hsb2) NameError: name 'hsb2' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 202 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[55], line 1 ----> 1 res = mod.fit() NameError: name 'mod' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 202 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[56], line 1 ----> 1 print(res.summary()) NameError: name 'res' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/contrasts.rst at block ending on line 237 Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[60], line 1 ----> 1 mod = ols("write ~ C(race, Simple)", data=hsb2) 2 res = mod.fit() 3 print(res.summary()) NameError: name 'hsb2' is not defined <<<------------------------------------------------------------------------- /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/model.py:docstring of statsmodels.base.model.GenericLikelihoodModelResults.aic:1: WARNING: duplicate object description of statsmodels.base.model.GenericLikelihoodModelResults.aic, other instance in dev/generated/statsmodels.base.model.GenericLikelihoodModelResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/model.py:docstring of statsmodels.base.model.GenericLikelihoodModelResults.bic:1: WARNING: duplicate object description of statsmodels.base.model.GenericLikelihoodModelResults.bic, other instance in dev/generated/statsmodels.base.model.GenericLikelihoodModelResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/model.py:docstring of statsmodels.base.model.GenericLikelihoodModelResults.bse:1: WARNING: duplicate object description of statsmodels.base.model.GenericLikelihoodModelResults.bse, other instance in dev/generated/statsmodels.base.model.GenericLikelihoodModelResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/model.py:docstring of statsmodels.base.model.GenericLikelihoodModelResults.llf:1: WARNING: duplicate object description of statsmodels.base.model.GenericLikelihoodModelResults.llf, other instance in dev/generated/statsmodels.base.model.GenericLikelihoodModelResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/model.py:docstring of statsmodels.base.model.LikelihoodModelResults.tvalues:1: WARNING: duplicate object description of statsmodels.base.model.LikelihoodModelResults.tvalues, other instance in dev/generated/statsmodels.base.model.LikelihoodModelResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/model.py:docstring of statsmodels.base.model.Model.endog_names:1: WARNING: duplicate object description of statsmodels.base.model.Model.endog_names, other instance in dev/generated/statsmodels.base.model.Model, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/model.py:docstring of statsmodels.base.model.Model.exog_names:1: WARNING: duplicate object description of statsmodels.base.model.Model.exog_names, other instance in dev/generated/statsmodels.base.model.Model, use :no-index: for one of them WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- ConnectionRefusedError Traceback (most recent call last) File /usr/lib/python3.13/urllib/request.py:1319, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1318 try: -> 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error File /usr/lib/python3.13/http/client.py:1338, in HTTPConnection.request(self, method, url, body, headers, encode_chunked) 1337 """Send a complete request to the server.""" -> 1338 self._send_request(method, url, body, headers, encode_chunked) File /usr/lib/python3.13/http/client.py:1384, in HTTPConnection._send_request(self, method, url, body, headers, encode_chunked) 1383 body = _encode(body, 'body') -> 1384 self.endheaders(body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1333, in HTTPConnection.endheaders(self, message_body, encode_chunked) 1332 raise CannotSendHeader() -> 1333 self._send_output(message_body, encode_chunked=encode_chunked) File /usr/lib/python3.13/http/client.py:1093, in HTTPConnection._send_output(self, message_body, encode_chunked) 1092 del self._buffer[:] -> 1093 self.send(msg) 1095 if message_body is not None: 1096 1097 # create a consistent interface to message_body File /usr/lib/python3.13/http/client.py:1037, in HTTPConnection.send(self, data) 1036 if self.auto_open: -> 1037 self.connect() 1038 else: File /usr/lib/python3.13/http/client.py:1472, in HTTPSConnection.connect(self) 1470 "Connect to a host on a given (SSL) port." -> 1472 super().connect() 1474 if self._tunnel_host: File /usr/lib/python3.13/http/client.py:1003, in HTTPConnection.connect(self) 1002 sys.audit("http.client.connect", self, self.host, self.port) -> 1003 self.sock = self._create_connection( 1004 (self.host,self.port), self.timeout, self.source_address) 1005 # Might fail in OSs that don't implement TCP_NODELAY File /usr/lib/python3.13/socket.py:864, in create_connection(address, timeout, source_address, all_errors) 863 if not all_errors: --> 864 raise exceptions[0] 865 raise ExceptionGroup("create_connection failed", exceptions) File /usr/lib/python3.13/socket.py:849, in create_connection(address, timeout, source_address, all_errors) 848 sock.bind(source_address) --> 849 sock.connect(sa) 850 # Break explicitly a reference cycle ConnectionRefusedError: [Errno 111] Connection refused During handling of the above exception, another exception occurred: URLError Traceback (most recent call last) Cell In[2], line 1 ----> 1 data = sm.datasets.get_rdataset("flchain", "survival", cache=True).data File /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/datasets/utils.py:237, in get_rdataset(dataname, package, cache) 234 docs_base_url = ("https://raw.githubusercontent.com/vincentarelbundock/Rdatasets/" 235 "master/doc/"+package+"/rst/") 236 cache = _get_cache(cache) --> 237 data, from_cache = _get_data(data_base_url, dataname, cache) 238 data = read_csv(data, index_col=0) 239 data = _maybe_reset_index(data) File /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/datasets/utils.py:166, in _get_data(base_url, dataname, cache, extension) 164 url = base_url + (dataname + ".%s") % extension 165 try: --> 166 data, from_cache = _urlopen_cached(url, cache) 167 except HTTPError as err: 168 if '404' in str(err): File /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/datasets/utils.py:157, in _urlopen_cached(url, cache) 155 # not using the cache or did not find it in cache 156 if not from_cache: --> 157 data = urlopen(url, timeout=3).read() 158 if cache is not None: # then put it in the cache 159 _cache_it(data, cache_path) File /usr/lib/python3.13/urllib/request.py:189, in urlopen(url, data, timeout, context) 187 else: 188 opener = _opener --> 189 return opener.open(url, data, timeout) File /usr/lib/python3.13/urllib/request.py:489, in OpenerDirector.open(self, fullurl, data, timeout) 486 req = meth(req) 488 sys.audit('urllib.Request', req.full_url, req.data, req.headers, req.get_method()) --> 489 response = self._open(req, data) 491 # post-process response 492 meth_name = protocol+"_response" File /usr/lib/python3.13/urllib/request.py:506, in OpenerDirector._open(self, req, data) 503 return result 505 protocol = req.type --> 506 result = self._call_chain(self.handle_open, protocol, protocol + 507 '_open', req) 508 if result: 509 return result File /usr/lib/python3.13/urllib/request.py:466, in OpenerDirector._call_chain(self, chain, kind, meth_name, *args) 464 for handler in handlers: 465 func = getattr(handler, meth_name) --> 466 result = func(*args) 467 if result is not None: 468 return result File /usr/lib/python3.13/urllib/request.py:1367, in HTTPSHandler.https_open(self, req) 1366 def https_open(self, req): -> 1367 return self.do_open(http.client.HTTPSConnection, req, 1368 context=self._context) File /usr/lib/python3.13/urllib/request.py:1322, in AbstractHTTPHandler.do_open(self, http_class, req, **http_conn_args) 1319 h.request(req.get_method(), req.selector, req.data, headers, 1320 encode_chunked=req.has_header('Transfer-encoding')) 1321 except OSError as err: # timeout error -> 1322 raise URLError(err) 1323 r = h.getresponse() 1324 except: URLError: <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) Cell In[3], line 1 ----> 1 df = data.loc[data.sex == "F", :] AttributeError: 'Dataset' object has no attribute 'loc' <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- KeyError Traceback (most recent call last) File /usr/lib/python3/dist-packages/pandas/core/indexes/base.py:3805, in Index.get_loc(self, key) 3804 try: -> 3805 return self._engine.get_loc(casted_key) 3806 except KeyError as err: File /usr/lib/python3/dist-packages/pandas/_libs/index.pyx:167, in pandas._libs.index.IndexEngine.get_loc() File /usr/lib/python3/dist-packages/pandas/_libs/index.pyx:196, in pandas._libs.index.IndexEngine.get_loc() File pandas/_libs/hashtable_class_helper.pxi:7081, in pandas._libs.hashtable.PyObjectHashTable.get_item() File pandas/_libs/hashtable_class_helper.pxi:7089, in pandas._libs.hashtable.PyObjectHashTable.get_item() KeyError: 'futime' The above exception was the direct cause of the following exception: KeyError Traceback (most recent call last) Cell In[4], line 1 ----> 1 sf = sm.SurvfuncRight(df["futime"], df["death"]) File /usr/lib/python3/dist-packages/pandas/core/frame.py:4102, in DataFrame.__getitem__(self, key) 4100 if self.columns.nlevels > 1: 4101 return self._getitem_multilevel(key) -> 4102 indexer = self.columns.get_loc(key) 4103 if is_integer(indexer): 4104 indexer = [indexer] File /usr/lib/python3/dist-packages/pandas/core/indexes/base.py:3812, in Index.get_loc(self, key) 3807 if isinstance(casted_key, slice) or ( 3808 isinstance(casted_key, abc.Iterable) 3809 and any(isinstance(x, slice) for x in casted_key) 3810 ): 3811 raise InvalidIndexError(key) -> 3812 raise KeyError(key) from err 3813 except TypeError: 3814 # If we have a listlike key, _check_indexing_error will raise 3815 # InvalidIndexError. Otherwise we fall through and re-raise 3816 # the TypeError. 3817 self._check_indexing_error(key) KeyError: 'futime' <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[5], line 1 ----> 1 sf.summary().head() NameError: name 'sf' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[6], line 1 ----> 1 sf.quantile(0.25) NameError: name 'sf' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[7], line 1 ----> 1 sf.quantile_ci(0.25) NameError: name 'sf' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[8], line 1 ----> 1 sf.plot() NameError: name 'sf' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[9], line 1 ----> 1 fig = sf.plot() NameError: name 'sf' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- IndexError Traceback (most recent call last) Cell In[10], line 1 ----> 1 ax = fig.get_axes()[0] IndexError: list index out of range <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[11], line 1 ----> 1 pt = ax.get_lines()[1] NameError: name 'ax' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[12], line 1 ----> 1 pt.set_visible(False) NameError: name 'pt' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[13], line 1 ----> 1 fig = sf.plot() NameError: name 'sf' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[14], line 1 ----> 1 lcb, ucb = sf.simultaneous_cb() NameError: name 'sf' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- IndexError Traceback (most recent call last) Cell In[15], line 1 ----> 1 ax = fig.get_axes()[0] IndexError: list index out of range <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[16], line 1 ----> 1 ax.fill_between(sf.surv_times, lcb, ucb, color='lightgrey') NameError: name 'ax' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[17], line 1 ----> 1 ax.set_xlim(365, 365*10) NameError: name 'ax' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[18], line 1 ----> 1 ax.set_ylim(0.7, 1) NameError: name 'ax' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[19], line 1 ----> 1 ax.set_ylabel("Proportion alive") NameError: name 'ax' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[20], line 1 ----> 1 ax.set_xlabel("Days since enrollment") NameError: name 'ax' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) Cell In[22], line 1 ----> 1 gb = data.groupby("sex") AttributeError: 'Dataset' object has no attribute 'groupby' <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- NameError Traceback (most recent call last) Cell In[25], line 1 ----> 1 for g in gb: 2 sexes.append(g[0]) 3 sf = sm.SurvfuncRight(g[1]["futime"], g[1]["death"]) NameError: name 'gb' is not defined <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- IndexError Traceback (most recent call last) Cell In[27], line 1 ----> 1 li[1].set_visible(False) IndexError: list index out of range <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- IndexError Traceback (most recent call last) Cell In[28], line 1 ----> 1 li[3].set_visible(False) IndexError: list index out of range <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- IndexError Traceback (most recent call last) Cell In[29], line 1 ----> 1 plt.figlegend((li[0], li[2]), sexes, loc="center right") IndexError: list index out of range <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) Cell In[33], line 1 ----> 1 stat, pv = sm.duration.survdiff(data.futime, data.death, data.sex) AttributeError: 'Dataset' object has no attribute 'futime' <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) Cell In[34], line 1 ----> 1 stat, pv = sm.duration.survdiff(data.futime, data.death, data.sex, weight_type='fh', fh_p=1) AttributeError: 'Dataset' object has no attribute 'futime' <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) Cell In[35], line 1 ----> 1 stat, pv = sm.duration.survdiff(data.futime, data.death, data.sex, weight_type='gb') AttributeError: 'Dataset' object has no attribute 'futime' <<<------------------------------------------------------------------------- WARNING: >>>------------------------------------------------------------------------- Exception in /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/duration.rst at block ending on line None Specify :okexcept: as an option in the ipython:: block to suppress this message --------------------------------------------------------------------------- AttributeError Traceback (most recent call last) Cell In[36], line 1 ----> 1 stat, pv = sm.duration.survdiff(data.futime, data.death, data.sex, weight_type='tw') AttributeError: 'Dataset' object has no attribute 'futime' <<<------------------------------------------------------------------------- /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/formulas.ipynb:211: WARNING: File not found: 'examples/notebooks/generated/regression_diagnostics.html' [nbsphinx.localfile] /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/examples/notebooks/generated/formulas.ipynb:564: WARNING: File not found: 'examples/notebooks/generated/contrasts.html' [nbsphinx.localfile] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/count_model.py:docstring of statsmodels.discrete.count_model.ZeroInflatedGeneralizedPoissonResults.llf:1: WARNING: duplicate object description of statsmodels.discrete.count_model.ZeroInflatedGeneralizedPoissonResults.llf, other instance in generated/statsmodels.discrete.count_model.ZeroInflatedGeneralizedPoissonResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/count_model.py:docstring of statsmodels.discrete.count_model.ZeroInflatedNegativeBinomialResults.llf:1: WARNING: duplicate object description of statsmodels.discrete.count_model.ZeroInflatedNegativeBinomialResults.llf, other instance in generated/statsmodels.discrete.count_model.ZeroInflatedNegativeBinomialResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/count_model.py:docstring of statsmodels.discrete.count_model.ZeroInflatedPoissonResults.llf:1: WARNING: duplicate object description of statsmodels.discrete.count_model.ZeroInflatedPoissonResults.llf, other instance in generated/statsmodels.discrete.count_model.ZeroInflatedPoissonResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/discrete_model.py:docstring of statsmodels.discrete.discrete_model.BinaryResults.llf:1: WARNING: duplicate object description of statsmodels.discrete.discrete_model.BinaryResults.llf, other instance in generated/statsmodels.discrete.discrete_model.BinaryResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/discrete_model.py:docstring of statsmodels.discrete.discrete_model.CountResults.llf:1: WARNING: duplicate object description of statsmodels.discrete.discrete_model.CountResults.llf, other instance in generated/statsmodels.discrete.discrete_model.CountResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/discrete_model.py:docstring of statsmodels.discrete.discrete_model.DiscreteResults.llf:1: WARNING: duplicate object description of statsmodels.discrete.discrete_model.DiscreteResults.llf, other instance in generated/statsmodels.discrete.discrete_model.DiscreteResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/discrete_model.py:docstring of statsmodels.discrete.discrete_model.GeneralizedPoissonResults.llf:1: WARNING: duplicate object description of statsmodels.discrete.discrete_model.GeneralizedPoissonResults.llf, other instance in generated/statsmodels.discrete.discrete_model.GeneralizedPoissonResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/discrete_model.py:docstring of statsmodels.discrete.discrete_model.LogitResults.llf:1: WARNING: duplicate object description of statsmodels.discrete.discrete_model.LogitResults.llf, other instance in generated/statsmodels.discrete.discrete_model.LogitResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/discrete_model.py:docstring of statsmodels.discrete.discrete_model.MultinomialResults.llf:1: WARNING: duplicate object description of statsmodels.discrete.discrete_model.MultinomialResults.llf, other instance in generated/statsmodels.discrete.discrete_model.MultinomialResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/discrete_model.py:docstring of statsmodels.discrete.discrete_model.NegativeBinomialResults.llf:1: WARNING: duplicate object description of statsmodels.discrete.discrete_model.NegativeBinomialResults.llf, other instance in generated/statsmodels.discrete.discrete_model.NegativeBinomialResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/discrete_model.py:docstring of statsmodels.discrete.discrete_model.ProbitResults.llf:1: WARNING: duplicate object description of statsmodels.discrete.discrete_model.ProbitResults.llf, other instance in generated/statsmodels.discrete.discrete_model.ProbitResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/truncated_model.py:docstring of statsmodels.discrete.truncated_model.HurdleCountResults.llf:1: WARNING: duplicate object description of statsmodels.discrete.truncated_model.HurdleCountResults.llf, other instance in generated/statsmodels.discrete.truncated_model.HurdleCountResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/truncated_model.py:docstring of statsmodels.discrete.truncated_model.TruncatedLFPoissonResults.llf:1: WARNING: duplicate object description of statsmodels.discrete.truncated_model.TruncatedLFPoissonResults.llf, other instance in generated/statsmodels.discrete.truncated_model.TruncatedLFPoissonResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/truncated_model.py:docstring of statsmodels.discrete.truncated_model.TruncatedNegativeBinomialResults.llf:1: WARNING: duplicate object description of statsmodels.discrete.truncated_model.TruncatedNegativeBinomialResults.llf, other instance in generated/statsmodels.discrete.truncated_model.TruncatedNegativeBinomialResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/distributions/copula/elliptical.py:docstring of statsmodels.distributions.copula.elliptical.GaussianCopula:46: WARNING: Footnote [1] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/distributions/copula/elliptical.py:docstring of statsmodels.distributions.copula.elliptical.StudentTCopula:24: WARNING: Footnote [1] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/duration/hazard_regression.py:docstring of statsmodels.duration.hazard_regression.PHRegResults.bse:1: WARNING: duplicate object description of statsmodels.duration.hazard_regression.PHRegResults.bse, other instance in generated/statsmodels.duration.hazard_regression.PHRegResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/model.py:docstring of statsmodels.base.model.LikelihoodModelResults.normalized_cov_params:1: WARNING: duplicate object description of statsmodels.duration.hazard_regression.PHRegResults.normalized_cov_params, other instance in generated/statsmodels.duration.hazard_regression.PHRegResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/gam/generalized_additive_model.py:docstring of statsmodels.gam.generalized_additive_model.GLMGamResults.cv:1: WARNING: duplicate object description of statsmodels.gam.generalized_additive_model.GLMGamResults.cv, other instance in generated/statsmodels.gam.generalized_additive_model.GLMGamResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/gam/generalized_additive_model.py:docstring of statsmodels.gam.generalized_additive_model.GLMGamResults.edf:1: WARNING: duplicate object description of statsmodels.gam.generalized_additive_model.GLMGamResults.edf, other instance in generated/statsmodels.gam.generalized_additive_model.GLMGamResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/gam/generalized_additive_model.py:docstring of statsmodels.gam.generalized_additive_model.GLMGamResults.gcv:1: WARNING: duplicate object description of statsmodels.gam.generalized_additive_model.GLMGamResults.gcv, other instance in generated/statsmodels.gam.generalized_additive_model.GLMGamResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/gam/generalized_additive_model.py:docstring of statsmodels.gam.generalized_additive_model.GLMGamResults.hat_matrix_diag:1: WARNING: duplicate object description of statsmodels.gam.generalized_additive_model.GLMGamResults.hat_matrix_diag, other instance in generated/statsmodels.gam.generalized_additive_model.GLMGamResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/generalized_linear_model.py:docstring of statsmodels.genmod.generalized_linear_model.GLMResults.plot_ceres_residuals:47: WARNING: Footnote [1] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/generalized_linear_model.py:docstring of statsmodels.genmod.generalized_linear_model.GLMResults.plot_ceres_residuals:51: WARNING: Footnote [2] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/families/family.py:docstring of statsmodels.genmod.families.family.Binomial.link:1: WARNING: duplicate object description of statsmodels.genmod.families.family.Binomial.link, other instance in generated/statsmodels.genmod.families.family.Binomial, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/families/family.py:docstring of statsmodels.genmod.families.family.Binomial.variance:1: WARNING: duplicate object description of statsmodels.genmod.families.family.Binomial.variance, other instance in generated/statsmodels.genmod.families.family.Binomial, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/families/family.py:docstring of statsmodels.genmod.families.family.Gamma.link:1: WARNING: duplicate object description of statsmodels.genmod.families.family.Gamma.link, other instance in generated/statsmodels.genmod.families.family.Gamma, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/families/family.py:docstring of statsmodels.genmod.families.family.Gamma.variance:1: WARNING: duplicate object description of statsmodels.genmod.families.family.Gamma.variance, other instance in generated/statsmodels.genmod.families.family.Gamma, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/families/family.py:docstring of statsmodels.genmod.families.family.Gaussian.link:1: WARNING: duplicate object description of statsmodels.genmod.families.family.Gaussian.link, other instance in generated/statsmodels.genmod.families.family.Gaussian, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/families/family.py:docstring of statsmodels.genmod.families.family.Gaussian.variance:1: WARNING: duplicate object description of statsmodels.genmod.families.family.Gaussian.variance, other instance in generated/statsmodels.genmod.families.family.Gaussian, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/families/family.py:docstring of statsmodels.genmod.families.family.InverseGaussian.link:1: WARNING: duplicate object description of statsmodels.genmod.families.family.InverseGaussian.link, other instance in generated/statsmodels.genmod.families.family.InverseGaussian, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/families/family.py:docstring of 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other instance in generated/statsmodels.genmod.families.family.NegativeBinomial, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/families/family.py:docstring of statsmodels.genmod.families.family.Poisson.link:1: WARNING: duplicate object description of statsmodels.genmod.families.family.Poisson.link, other instance in generated/statsmodels.genmod.families.family.Poisson, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/families/family.py:docstring of statsmodels.genmod.families.family.Poisson.variance:1: WARNING: duplicate object description of statsmodels.genmod.families.family.Poisson.variance, other instance in generated/statsmodels.genmod.families.family.Poisson, use :no-index: for one of them 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[ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/regression/mixed_linear_model.py:docstring of statsmodels.regression.mixed_linear_model.MixedLMResults.bse_fe:1: WARNING: duplicate object description of statsmodels.regression.mixed_linear_model.MixedLMResults.bse_fe, other instance in generated/statsmodels.regression.mixed_linear_model.MixedLMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/regression/mixed_linear_model.py:docstring of statsmodels.regression.mixed_linear_model.MixedLMResults.bse_re:1: WARNING: duplicate object description of statsmodels.regression.mixed_linear_model.MixedLMResults.bse_re, other instance in generated/statsmodels.regression.mixed_linear_model.MixedLMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/model.py:docstring of statsmodels.base.model.LikelihoodModelResults.normalized_cov_params:1: WARNING: duplicate object description of statsmodels.regression.mixed_linear_model.MixedLMResults.normalized_cov_params, other instance in generated/statsmodels.regression.mixed_linear_model.MixedLMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/regression/recursive_ls.py:docstring of statsmodels.regression.recursive_ls.RecursiveLS:27: WARNING: Footnote [*] is not referenced. 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[ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/robust_linear_model.py:docstring of statsmodels.robust.robust_linear_model.RLMResults.bcov_scaled:1: WARNING: duplicate object description of statsmodels.robust.robust_linear_model.RLMResults.bcov_scaled, other instance in generated/statsmodels.robust.robust_linear_model.RLMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/robust_linear_model.py:docstring of statsmodels.robust.robust_linear_model.RLMResults.bcov_unscaled:1: WARNING: duplicate object description of statsmodels.robust.robust_linear_model.RLMResults.bcov_unscaled, other instance in generated/statsmodels.robust.robust_linear_model.RLMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/robust_linear_model.py:docstring of statsmodels.robust.robust_linear_model.RLMResults.bse:1: WARNING: duplicate object description of statsmodels.robust.robust_linear_model.RLMResults.bse, other instance in generated/statsmodels.robust.robust_linear_model.RLMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/robust_linear_model.py:docstring of statsmodels.robust.robust_linear_model.RLMResults.chisq:1: WARNING: duplicate object description of statsmodels.robust.robust_linear_model.RLMResults.chisq, other instance in generated/statsmodels.robust.robust_linear_model.RLMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/robust_linear_model.py:docstring of statsmodels.robust.robust_linear_model.RLMResults.fittedvalues:1: WARNING: duplicate object description of statsmodels.robust.robust_linear_model.RLMResults.fittedvalues, other instance in generated/statsmodels.robust.robust_linear_model.RLMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/model.py:docstring of statsmodels.base.model.LikelihoodModelResults.normalized_cov_params:1: WARNING: duplicate object description of statsmodels.robust.robust_linear_model.RLMResults.normalized_cov_params, other instance in generated/statsmodels.robust.robust_linear_model.RLMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/robust_linear_model.py:docstring of statsmodels.robust.robust_linear_model.RLMResults.pvalues:1: WARNING: duplicate object description of statsmodels.robust.robust_linear_model.RLMResults.pvalues, other instance in generated/statsmodels.robust.robust_linear_model.RLMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/robust_linear_model.py:docstring of statsmodels.robust.robust_linear_model.RLMResults.resid:1: WARNING: duplicate object description of statsmodels.robust.robust_linear_model.RLMResults.resid, other instance in generated/statsmodels.robust.robust_linear_model.RLMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/robust_linear_model.py:docstring of statsmodels.robust.robust_linear_model.RLMResults.sresid:1: WARNING: duplicate object description of statsmodels.robust.robust_linear_model.RLMResults.sresid, other instance in generated/statsmodels.robust.robust_linear_model.RLMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/robust_linear_model.py:docstring of statsmodels.robust.robust_linear_model.RLMResults.tvalues:1: WARNING: duplicate object description of statsmodels.robust.robust_linear_model.RLMResults.tvalues, other instance in generated/statsmodels.robust.robust_linear_model.RLMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/robust_linear_model.py:docstring of statsmodels.robust.robust_linear_model.RLMResults.weights:1: WARNING: duplicate object description of statsmodels.robust.robust_linear_model.RLMResults.weights, other instance in generated/statsmodels.robust.robust_linear_model.RLMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/stats/multicomp.py:docstring of statsmodels.sandbox.stats.multicomp.TukeyHSDResults.plot_simultaneous:37: WARNING: Footnote [*] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima_process.py:docstring of statsmodels.tsa.arima_process.ArmaProcess.acovf:19: WARNING: Footnote [*] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/anova.py:docstring of statsmodels.stats.anova.AnovaRM:46: WARNING: Footnote [*] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/correlation_tools.py:docstring of statsmodels.stats.correlation_tools.corr_nearest_factor:57: WARNING: Footnote [*] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/correlation_tools.py:docstring of statsmodels.stats.correlation_tools.kernel_covariance:36: WARNING: Footnote [1] is not referenced. 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[ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/outliers_influence.py:docstring of statsmodels.stats.outliers_influence.GLMInfluence.d_fittedvalues_scaled:1: WARNING: duplicate object description of statsmodels.stats.outliers_influence.GLMInfluence.d_fittedvalues_scaled, other instance in generated/statsmodels.stats.outliers_influence.GLMInfluence, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/outliers_influence.py:docstring of statsmodels.stats.outliers_influence.GLMInfluence.d_linpred:1: WARNING: duplicate object description of statsmodels.stats.outliers_influence.GLMInfluence.d_linpred, other instance in generated/statsmodels.stats.outliers_influence.GLMInfluence, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/outliers_influence.py:docstring of statsmodels.stats.outliers_influence.MLEInfluence.cooks_distance:1: WARNING: duplicate object description of statsmodels.stats.outliers_influence.MLEInfluence.cooks_distance, other instance in generated/statsmodels.stats.outliers_influence.MLEInfluence, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/outliers_influence.py:docstring of statsmodels.stats.outliers_influence.MLEInfluence.d_fittedvalues:1: WARNING: duplicate object description of statsmodels.stats.outliers_influence.MLEInfluence.d_fittedvalues, other instance in generated/statsmodels.stats.outliers_influence.MLEInfluence, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/outliers_influence.py:docstring of statsmodels.stats.outliers_influence.MLEInfluence.d_fittedvalues_scaled:1: WARNING: duplicate object description of statsmodels.stats.outliers_influence.MLEInfluence.d_fittedvalues_scaled, other instance in generated/statsmodels.stats.outliers_influence.MLEInfluence, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/outliers_influence.py:docstring of statsmodels.stats.outliers_influence.MLEInfluence.d_params:1: WARNING: duplicate object description of statsmodels.stats.outliers_influence.MLEInfluence.d_params, other instance in generated/statsmodels.stats.outliers_influence.MLEInfluence, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/outliers_influence.py:docstring of statsmodels.stats.outliers_influence.MLEInfluence.hat_matrix_diag:1: WARNING: duplicate object description of statsmodels.stats.outliers_influence.MLEInfluence.hat_matrix_diag, other instance in generated/statsmodels.stats.outliers_influence.MLEInfluence, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/outliers_influence.py:docstring of statsmodels.stats.outliers_influence.MLEInfluence.params_one:1: WARNING: duplicate object description of statsmodels.stats.outliers_influence.MLEInfluence.params_one, other instance in generated/statsmodels.stats.outliers_influence.MLEInfluence, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/outliers_influence.py:docstring of statsmodels.stats.outliers_influence.MLEInfluence.resid_studentized:1: WARNING: duplicate object description of statsmodels.stats.outliers_influence.MLEInfluence.resid_studentized, other instance in generated/statsmodels.stats.outliers_influence.MLEInfluence, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/docstring of statsmodels.stats.outliers_influence.OLSInfluence.cooks_distance:7: WARNING: Footnote [*] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/docstring of statsmodels.stats.outliers_influence.OLSInfluence.cooks_distance:9: WARNING: Footnote [*] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/proportion.py:docstring of statsmodels.stats.proportion.confint_proportions_2indep:54: WARNING: Footnote [1] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/proportion.py:docstring of statsmodels.stats.proportion.confint_proportions_2indep:58: WARNING: Footnote [2] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/proportion.py:docstring of statsmodels.stats.proportion.confint_proportions_2indep:61: WARNING: Footnote [3] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/proportion.py:docstring of statsmodels.stats.proportion.confint_proportions_2indep:63: WARNING: Footnote [4] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/proportion.py:docstring of statsmodels.stats.proportion.confint_proportions_2indep:68: WARNING: Footnote [5] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/proportion.py:docstring of statsmodels.stats.proportion.proportion_confint:48: WARNING: Footnote [*] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/proportion.py:docstring of statsmodels.stats.proportion.proportion_confint:50: WARNING: Footnote [*] is not referenced. 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[ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/simulation_smoother.py:docstring of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.generated_measurement_disturbance:1: WARNING: duplicate object description of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.generated_measurement_disturbance, other instance in generated/statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/simulation_smoother.py:docstring of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.generated_obs:1: WARNING: duplicate object description of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.generated_obs, other instance in 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statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.generated_state_disturbance, other instance in generated/statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/simulation_smoother.py:docstring of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.simulate_all:1: WARNING: duplicate object description of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.simulate_all, other instance in generated/statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/simulation_smoother.py:docstring of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.simulate_disturbance:1: WARNING: duplicate object description of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.simulate_disturbance, other instance in generated/statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/simulation_smoother.py:docstring of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.simulate_state:1: WARNING: duplicate object description of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.simulate_state, other instance in generated/statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/simulation_smoother.py:docstring of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.simulated_measurement_disturbance:1: WARNING: duplicate object description of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.simulated_measurement_disturbance, other instance in generated/statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/simulation_smoother.py:docstring of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.simulated_state:1: WARNING: duplicate object description of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.simulated_state, other instance in generated/statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/simulation_smoother.py:docstring of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.simulated_state_disturbance:1: WARNING: duplicate object description of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.simulated_state_disturbance, other instance in generated/statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/simulation_smoother.py:docstring of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.simulation_output:1: WARNING: duplicate object description of statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults.simulation_output, other instance in generated/statsmodels.tsa.statespace.simulation_smoother.SimulationSmoothResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/mlemodel.py:docstring of statsmodels.tsa.statespace.mlemodel.MLEResults.info_criteria:41: WARNING: Footnote [*] is not referenced. 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[ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/svar_model.py:docstring of statsmodels.tsa.vector_ar.svar_model.SVARResults:133: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.k_ar, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/svar_model.py:docstring of statsmodels.tsa.vector_ar.svar_model.SVARResults:139: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.params, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/svar_model.py:docstring of statsmodels.tsa.vector_ar.svar_model.SVARResults:149: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.names, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/svar_model.py:docstring of statsmodels.tsa.vector_ar.svar_model.SVARResults.aic:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.aic, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/svar_model.py:docstring of statsmodels.tsa.vector_ar.svar_model.SVARResults.bic:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.bic, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/svar_model.py:docstring of statsmodels.tsa.vector_ar.svar_model.SVARResults.bse:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.bse, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/var_model.py:docstring of statsmodels.tsa.vector_ar.var_model.VARResults.cov_params:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.cov_params, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/svar_model.py:docstring of statsmodels.tsa.vector_ar.svar_model.SVARResults.detomega:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.detomega, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/svar_model.py:docstring of statsmodels.tsa.vector_ar.svar_model.SVARResults.df_model:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.df_model, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/svar_model.py:docstring of statsmodels.tsa.vector_ar.svar_model.SVARResults.df_resid:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.df_resid, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/svar_model.py:docstring of statsmodels.tsa.vector_ar.svar_model.SVARResults.fittedvalues:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.fittedvalues, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/svar_model.py:docstring of statsmodels.tsa.vector_ar.svar_model.SVARResults.fpe:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.fpe, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/svar_model.py:docstring of statsmodels.tsa.vector_ar.svar_model.SVARResults.info_criteria:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.info_criteria, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/var_model.py:docstring of statsmodels.tsa.vector_ar.var_model.VARResults.irf_resim:21: WARNING: Footnote [*] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/svar_model.py:docstring of statsmodels.tsa.vector_ar.svar_model.SVARResults.llf:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.llf, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/svar_model.py:docstring of statsmodels.tsa.vector_ar.svar_model.SVARResults.resid:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.resid, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/svar_model.py:docstring of statsmodels.tsa.vector_ar.svar_model.SVARResults.sigma_u_mle:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.sigma_u_mle, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/svar_model.py:docstring of statsmodels.tsa.vector_ar.svar_model.SVARResults.stderr:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.stderr, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/svar_model.py:docstring of statsmodels.tsa.vector_ar.svar_model.SVARResults.tvalues:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.svar_model.SVARResults.tvalues, other instance in generated/statsmodels.tsa.vector_ar.svar_model.SVARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/var_model.py:docstring of statsmodels.tsa.vector_ar.var_model.VARResults:80: WARNING: duplicate object description of statsmodels.tsa.vector_ar.var_model.VARResults.params, other instance in generated/statsmodels.tsa.vector_ar.var_model.VARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/var_model.py:docstring of statsmodels.tsa.vector_ar.var_model.VARResults:86: WARNING: duplicate object description of statsmodels.tsa.vector_ar.var_model.VARResults.names, other instance in generated/statsmodels.tsa.vector_ar.var_model.VARResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/var_model.py:docstring of statsmodels.tsa.vector_ar.var_model.VARResults.irf_resim:21: WARNING: Footnote [*] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.cov_params_wo_det:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.cov_params_wo_det, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.cov_var_repr:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.cov_var_repr, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.fittedvalues:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.fittedvalues, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.llf:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.llf, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.pvalues_alpha:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.pvalues_alpha, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.pvalues_beta:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.pvalues_beta, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.pvalues_det_coef:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.pvalues_det_coef, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.pvalues_det_coef_coint:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.pvalues_det_coef_coint, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.pvalues_gamma:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.pvalues_gamma, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.resid:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.resid, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.stderr_alpha:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.stderr_alpha, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.stderr_beta:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.stderr_beta, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.stderr_coint:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.stderr_coint, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.stderr_det_coef:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.stderr_det_coef, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.stderr_det_coef_coint:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.stderr_det_coef_coint, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.stderr_gamma:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.stderr_gamma, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.stderr_params:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.stderr_params, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.tvalues_alpha:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.tvalues_alpha, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.tvalues_beta:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.tvalues_beta, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.tvalues_det_coef:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.tvalues_det_coef, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.tvalues_det_coef_coint:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.tvalues_det_coef_coint, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.tvalues_gamma:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.tvalues_gamma, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.VECMResults.var_rep:1: WARNING: duplicate object description of statsmodels.tsa.vector_ar.vecm.VECMResults.var_rep, other instance in generated/statsmodels.tsa.vector_ar.vecm.VECMResults, use :no-index: for one of them /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/vecm.py:docstring of statsmodels.tsa.vector_ar.vecm.coint_johansen:29: WARNING: Footnote [1] is not referenced. [ref.footnote] /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/glm.rst:6: WARNING: Duplicate explicit target name: "glm". [docutils] /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/glm.rst:144: WARNING: duplicate object description of statsmodels.genmod.families.family, other instance in gee, use :no-index: for one of them looking for now-outdated files... none found pickling environment... done checking consistency... /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.family.Binomial.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.family.Binomial /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.family.Family.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.family.Family /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.family.Gamma.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.family.Gamma /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.family.Gaussian.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.family.Gaussian /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.family.InverseGaussian.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.family.InverseGaussian /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.family.NegativeBinomial.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.family.NegativeBinomial /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.family.Poisson.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.family.Poisson /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.family.Tweedie.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.family.Tweedie /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.links.CDFLink.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.links.CDFLink /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.links.CLogLog.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.links.CLogLog /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.links.Cauchy.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.links.Cauchy /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.links.Identity.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.links.Identity /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.links.InversePower.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.links.InversePower /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.links.InverseSquared.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.links.InverseSquared /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.links.Link.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.links.Link /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.links.Log.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.links.Log /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.links.Logit.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.links.Logit /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.links.NegativeBinomial.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.links.NegativeBinomial /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.links.Power.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.links.Power /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.genmod.families.links.Probit.rst: document is referenced in multiple toctrees: ['gee', 'glm'], selecting: glm <- generated/statsmodels.genmod.families.links.Probit /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.stats.knockoff_regeffects.OLSEffects.rst: document is referenced in multiple toctrees: ['stats', 'stats'], selecting: stats <- generated/statsmodels.stats.knockoff_regeffects.OLSEffects /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.stats.proportion.proportion_effectsize.rst: document is referenced in multiple toctrees: ['stats', 'stats'], selecting: stats <- generated/statsmodels.stats.proportion.proportion_effectsize /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.statespace.exponential_smoothing.ExponentialSmoothing.rst: document is referenced in multiple toctrees: ['statespace', 'tsa'], selecting: tsa <- generated/statsmodels.tsa.statespace.exponential_smoothing.ExponentialSmoothing /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.statespace.exponential_smoothing.ExponentialSmoothingResults.rst: document is referenced in multiple toctrees: ['statespace', 'tsa'], selecting: tsa <- generated/statsmodels.tsa.statespace.exponential_smoothing.ExponentialSmoothingResults /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.hypothesis_test_results.HypothesisTestResults.rst: document is referenced in multiple toctrees: ['vector_ar', 'vector_ar'], selecting: vector_ar <- generated/statsmodels.tsa.vector_ar.hypothesis_test_results.HypothesisTestResults /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.hypothesis_test_results.NormalityTestResults.rst: document is referenced in multiple toctrees: ['vector_ar', 'vector_ar'], selecting: vector_ar <- generated/statsmodels.tsa.vector_ar.hypothesis_test_results.NormalityTestResults /build/reproducible-path/statsmodels-0.14.5+dfsg/docs/source/generated/statsmodels.tsa.vector_ar.hypothesis_test_results.WhitenessTestResults.rst: document is referenced in multiple toctrees: ['vector_ar', 'vector_ar'], selecting: vector_ar <- generated/statsmodels.tsa.vector_ar.hypothesis_test_results.WhitenessTestResults done preparing documents... 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The HTML pages are in build/html. make[2]: Leaving directory '/build/reproducible-path/statsmodels-0.14.5+dfsg/docs' mv docs/build/* build/ : # replace timestamps and build paths in examples output for reproducibility for html in `find build/html examples -name _modules -prune -o -name "*.html" -o -name "*.ipynb" -o -name "*.ipynb.txt"` ; do \ sed -i -e 's#/build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/[^/]*/build/statsmodels/#/usr/lib/python3/dist-packages/statsmodels/#g' \ -e 's# at 0x[0-9a-f]\{8,16\}\(>\|>\)# at 0xadde5de1e8ed\1#g' \ -e 's#tmp/ipykernel_[0-9]\+#tmp/ipykernel_nnnnnnn#g' \ -e 's#^\s\+.\(iopub.execute_input\|iopub.status.busy\|iopub.status.idle\|shell.execute_reply\).:.*# #g' \ -e 's#\(Date:.*\)[A-Z][a-z]\+, \+[0-9]\+,\? \+[A-Z][a-z]\+,\? \+[0-9]\+#\1Sun, 10 Aug 2025#g' \ -e 's#\(Time:.*\)[0-9][0-9]:[0-9][0-9]:[0-9][0-9]#\113:13:47#g' ${html} ; \ done sed: couldn't edit build/html/_modules: not a regular file rm -rf docs/source/generated/ make[1]: Leaving directory '/build/reproducible-path/statsmodels-0.14.5+dfsg' debian/rules override_dh_auto_test make[1]: Entering directory '/build/reproducible-path/statsmodels-0.14.5+dfsg' TEST_SUCCESS=true ; cd tools && for testpy3ver in `py3versions -vs` ; do \ for testpath in ../.pybuild/*${testpy3ver}*/*/statsmodels ; do \ PYTHONPATH=${testpath}/.. python${testpy3ver} -m pytest -v ${testpath} || TEST_SUCCESS=false ; \ rm -rf ${testpath}/.pytest_cache ; \ done ; done ; ${TEST_SUCCESS} ============================= test session starts ============================== platform linux -- Python 3.13.7, pytest-8.4.1, pluggy-1.6.0 -- /usr/bin/python3.13 cachedir: .pytest_cache rootdir: /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels configfile: setup.cfg plugins: forked-1.6.0, typeguard-4.4.4 collecting ... collected 17988 items ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/tests/test_data.py::TestArrays::test_orig PASSED [ 0%] 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../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_bic PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_predict PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_predict_xb PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_loglikeobs PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_jac PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_summary_latex PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_distr PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_pred_table PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_resid_dev PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_resid_generalized PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_resid_response PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNewton::test_init_kwargs PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_fit_regularized_invalid_method PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_params PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_conf_int PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_zstat PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_pvalues PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_cov_params PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_llf PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_llnull PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_llr PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_llr_pvalue PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_normalized_cov_params XFAIL [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_bse PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_dof PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_aic PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_bic PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_predict PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_predict_xb PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_loglikeobs PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_jac PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_summary_latex PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_distr PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_pred_table PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_resid_dev PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_resid_generalized PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBFGS::test_resid_response PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_fit_regularized_invalid_method PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_params PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_conf_int PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_zstat PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_pvalues PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_cov_params PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_llf PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_llnull PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_llr PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_llr_pvalue PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_normalized_cov_params XFAIL [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_bse PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_dof PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_aic PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_bic PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_predict PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_predict_xb PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_loglikeobs PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_jac PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_summary_latex PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_distr PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_pred_table PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_resid_dev PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_resid_generalized PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNM::test_resid_response PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_fit_regularized_invalid_method PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_params PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_conf_int PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_zstat PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_pvalues PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_cov_params PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_llf PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_llnull PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_llr PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_llr_pvalue PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_normalized_cov_params XFAIL [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_bse PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_dof PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_aic PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_bic PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_predict PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_predict_xb PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_loglikeobs PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_jac PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_summary_latex PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_distr PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_pred_table PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_resid_dev PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_resid_generalized PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitPowell::test_resid_response PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_fit_regularized_invalid_method PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_params PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_conf_int PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_zstat PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_pvalues PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_cov_params PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_llf PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_llnull PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_llr PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_llr_pvalue PASSED [ 3%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_normalized_cov_params XFAIL [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_bse PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_dof PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_aic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_bic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_predict PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_predict_xb PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_loglikeobs PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_jac PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_summary_latex PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_distr PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_pred_table PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_resid_dev PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_resid_generalized PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitCG::test_resid_response PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_fit_regularized_invalid_method PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_conf_int PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_zstat PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_pvalues PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_cov_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_llf PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_llnull PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_llr PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_llr_pvalue PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_normalized_cov_params XFAIL [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_bse PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_dof PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_aic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_bic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_predict PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_predict_xb PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_loglikeobs PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_jac PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_summary_latex PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_distr PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_pred_table PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_resid_dev PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_resid_generalized PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitNCG::test_resid_response PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_fit_regularized_invalid_method PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_conf_int PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_zstat PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_pvalues PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_cov_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_llf PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_llnull PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_llr PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_llr_pvalue PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_normalized_cov_params XFAIL [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_bse PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_dof PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_aic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_bic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_predict PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_predict_xb PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_loglikeobs PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_jac PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_summary_latex PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_distr PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_pred_table PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_resid_dev PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_resid_generalized PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitBasinhopping::test_resid_response PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_fit_regularized_invalid_method PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_conf_int PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_zstat PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_pvalues PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_cov_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_llf PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_llnull PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_llr PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_llr_pvalue PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_normalized_cov_params XFAIL [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_bse PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_dof PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_aic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_bic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_predict PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_predict_xb PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_loglikeobs PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_jac PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_summary_latex PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_distr PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_pred_table PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_resid_dev PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_resid_generalized PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDefault::test_resid_response PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_fit_regularized_invalid_method PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_conf_int PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_zstat PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_pvalues PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_cov_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_llf PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_llnull PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_llr PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_llr_pvalue PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_normalized_cov_params XFAIL [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_bse PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_dof PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_aic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_bic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_predict PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_predict_xb PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_loglikeobs PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_jac PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_summary_latex PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_distr PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_pred_table PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_resid_dev PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_resid_generalized PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeDogleg::test_resid_response PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_fit_regularized_invalid_method PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_conf_int PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_zstat PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_pvalues PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_cov_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_llf PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_llnull PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_llr PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_llr_pvalue PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_normalized_cov_params XFAIL [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_bse PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_dof PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_aic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_bic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_predict PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_predict_xb PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_loglikeobs PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_jac PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_summary_latex PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_distr PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_pred_table PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_resid_dev PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_resid_generalized PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitMinimizeAdditionalOptions::test_resid_response PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitL1::test_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitL1::test_conf_int PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitL1::test_bse PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitL1::test_nnz_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitL1::test_aic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitL1::test_bic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitL1::test_cov_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1::test_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1::test_conf_int PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1::test_bse PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1::test_nnz_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1::test_aic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1::test_bic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitL1::test_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitL1::test_conf_int PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitL1::test_bse PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitL1::test_nnz_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitL1::test_aic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitL1::test_bic PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitL1::test_cov_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestCVXOPT::test_cvxopt_versus_slsqp PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestSweepAlphaL1::test_sweep_alpha PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonL1Compatability::test_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonL1Compatability::test_cov_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonL1Compatability::test_df PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonL1Compatability::test_t_test PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonL1Compatability::test_f_test PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonL1Compatability::test_bad_r_matrix PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialL1Compatability::test_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialL1Compatability::test_cov_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialL1Compatability::test_df PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialL1Compatability::test_t_test PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialL1Compatability::test_f_test PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialL1Compatability::test_bad_r_matrix PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeoL1Compatability::test_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeoL1Compatability::test_cov_params PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeoL1Compatability::test_df PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeoL1Compatability::test_t_test PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeoL1Compatability::test_f_test PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeoL1Compatability::test_bad_r_matrix PASSED [ 4%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitL1Compatability::test_params PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitL1Compatability::test_cov_params PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitL1Compatability::test_df PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitL1Compatability::test_t_test PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitL1Compatability::test_f_test PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitL1Compatability::test_bad_r_matrix PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1Compatability::test_params PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1Compatability::test_cov_params PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1Compatability::test_df PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1Compatability::test_bad_r_matrix PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1Compatability::test_t_test PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitL1Compatability::test_f_test SKIPPED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitL1Compatability::test_params PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitL1Compatability::test_cov_params PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitL1Compatability::test_df PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitL1Compatability::test_t_test PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitL1Compatability::test_f_test PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestProbitL1Compatability::test_bad_r_matrix PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestL1AlphaZeroLogit::test_basic_results PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestL1AlphaZeroLogit::test_tests PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestL1AlphaZeroLogit::test_converged PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestL1AlphaZeroProbit::test_basic_results PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestL1AlphaZeroProbit::test_tests PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestL1AlphaZeroMNLogit::test_basic_results PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dydxmedian PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dydxzero PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dyexoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dyexmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dyexmedian PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_dyexzero PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eydxmedian PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eydxzero PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eyexoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eyexmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eyexmedian PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_eyexzero PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dummy_dydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dummy_dydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dummy_eydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dummy_eydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_count_dydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_count_dydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_count_dummy_dydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_count_dummy_dydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_fit_regularized_invalid_method PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_params PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_conf_int PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_zstat PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_pvalues PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_cov_params PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_llf PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_llnull PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_llr PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_llr_pvalue PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_normalized_cov_params XFAIL [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_bse PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dof PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_aic PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_bic PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_predict PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_predict_xb PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_loglikeobs PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_jac PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_summary_latex PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_distr PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_pred_table PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_resid_dev PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_resid_generalized PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_resid_response PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_resid_pearson PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_exog1 PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_nodummy_exog2 PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dummy_exog1 PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_dummy_exog2 PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewton::test_diagnostic PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dydxmedian PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dydxzero PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dyexoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dyexmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dyexmedian PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_dyexzero PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eydxmedian PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eydxzero PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eyexoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eyexmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eyexmedian PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_eyexzero PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_dydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_dydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_eydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_eydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_count_dydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_count_dydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_count_dummy_dydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_count_dummy_dydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_resid_pearson PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_exog1 PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_nodummy_exog2 PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_exog1 PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitNewtonPrepend::test_dummy_exog2 PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dydxmedian PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dydxzero PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dyexoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dyexmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dyexmedian PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_dyexzero PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eydxmedian PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eydxzero PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eyexoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eyexmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eyexmedian PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_nodummy_eyexzero PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_dummy_dydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_dummy_dydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_dummy_eydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_dummy_eydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_count_dydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_count_dydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_count_dummy_dydxoverall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_count_dummy_dydxmean PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_fit_regularized_invalid_method PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_params PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_conf_int PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_zstat PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_pvalues PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_cov_params PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_llf PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_llnull PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_llr PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_llr_pvalue PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_normalized_cov_params XFAIL [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_bse PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_dof PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_aic PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_bic PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_predict PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_predict_xb PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_loglikeobs PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_jac PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_summary_latex PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_distr PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_pred_table PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_resid_dev PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_resid_generalized PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestLogitBFGS::test_resid_response PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_fit_regularized_invalid_method PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_params PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_conf_int PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_zstat PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_pvalues PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_llf PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_llnull PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_llr PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_llr_pvalue PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_normalized_cov_params XFAIL [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_bse PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_dof PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_aic PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_bic PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_predict PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_predict_xb PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_loglikeobs PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_jac PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_summary_latex PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_distr PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_margeff_overall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_margeff_dummy_overall PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_resid PASSED [ 5%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_predict_prob PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNewton::test_cov_params XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_fit_regularized_invalid_method PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_cov_params SKIPPED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_llf PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_llnull PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_llr PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_llr_pvalue PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_normalized_cov_params XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_dof PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_aic PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_bic PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_loglikeobs PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_jac PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_summary_latex PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_distr PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_pvalues XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_bse PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_params PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_alpha PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_conf_int PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_zstat PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_fittedvalues PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_predict PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Newton::test_predict_xb PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_fit_regularized_invalid_method PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_cov_params SKIPPED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_llf PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_llnull PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_llr PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_llr_pvalue PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_normalized_cov_params XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_bse PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_dof PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_aic PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_bic PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_loglikeobs PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_jac PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_summary_latex PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_distr PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_pvalues XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_zstat PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_lnalpha PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_params PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_conf_int PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_predict XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Newton::test_predict_xb XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_fit_regularized_invalid_method PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_cov_params SKIPPED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_llf PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_llnull PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_llr PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_llr_pvalue PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_normalized_cov_params XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_dof PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_aic PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_bic PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_loglikeobs PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_jac PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_summary_latex PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_distr PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_pvalues XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_bse PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_params PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_alpha PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_conf_int PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_zstat PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_fittedvalues PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_predict PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2BFGS::test_predict_xb PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_fit_regularized_invalid_method PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_cov_params SKIPPED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_llf PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_llnull PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_llr PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_llr_pvalue PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_normalized_cov_params XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_bse PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_dof PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_aic PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_bic PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_loglikeobs PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_jac PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_summary_latex PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_distr PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_pvalues XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_zstat PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_lnalpha PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_params PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_conf_int PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_predict XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1BFGS::test_predict_xb XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_fit_regularized_invalid_method PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_cov_params SKIPPED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_llnull PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_llr_pvalue PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_normalized_cov_params XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_dof PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_loglikeobs PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_jac PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_summary_latex PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_distr PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_pvalues XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_aic PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_bic PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_conf_int PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_fittedvalues PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_predict PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_params PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_predict_xb PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_zstat PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_llf PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_llr PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialGeometricBFGS::test_bse PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_fit_regularized_invalid_method PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_params PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_conf_int PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_zstat PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_pvalues PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_llf PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_llnull PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_llr PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_llr_pvalue PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_normalized_cov_params XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_bse PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_dof PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_aic PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_bic PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_predict PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_predict_xb PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_loglikeobs PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_jac PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_summary_latex PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_margeff_overall PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_margeff_mean PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_margeff_dummy PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_j PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_k PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_endog_names PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_pred_table PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_resid PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_cov_params XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitNewtonBaseZero::test_distr XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_fit_regularized_invalid_method PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_params PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_conf_int PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_zstat PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_pvalues PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_llf PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_llnull PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_llr PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_llr_pvalue PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_normalized_cov_params XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_bse PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_dof PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_aic PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_bic PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_predict PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_predict_xb PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_loglikeobs PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_jac PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_summary_latex PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_margeff_overall PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_margeff_mean PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_margeff_dummy PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_j PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_k PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_endog_names PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_pred_table PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_resid PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_cov_params XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestMNLogitLBFGSBaseZero::test_distr XFAIL [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_mnlogit_basinhopping PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_perfect_prediction PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_poisson_predict PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_poisson_newton PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_issue_339 PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_issue_341 PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_negative_binomial_default_alpha_param PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_iscount PASSED [ 6%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_isdummy PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_non_binary PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_mnlogit_factor PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_mnlogit_factor_categorical PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_formula_missing_exposure PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_predict_with_exposure PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_binary_pred_table_zeros PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_bse PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_params PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_alpha PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_conf_int PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_aic PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_bic PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_df PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_llf PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_wald PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_t PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_jac PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p2::test_distr PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_bse PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_params PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_alpha PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_conf_int PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_aic PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_bic PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_df PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_transparams::test_llf PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_llf PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_score PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_hessian PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_t PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_fit_regularized PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_init_kwds PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_distr PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_underdispersion::test_basic PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_underdispersion::test_newton PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_underdispersion::test_mean_var PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_underdispersion::test_predict_prob PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_underdispersion::test_jac PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoisson_underdispersion::test_distr PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_fit_regularized_invalid_method PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_cov_params SKIPPED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_llf PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_llnull PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_llr PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_llr_pvalue PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_normalized_cov_params XFAIL [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_dof PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_aic PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_bic PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_loglikeobs PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_jac PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_summary_latex PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_distr PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_pvalues XFAIL [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_bse PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_params PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_alpha PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_conf_int PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_zstat PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_fittedvalues PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_predict PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2Newton::test_predict_xb PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_fit_regularized_invalid_method PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_cov_params SKIPPED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_llf PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_llnull PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_llr PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_llr_pvalue PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_normalized_cov_params XFAIL [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_bse PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_dof PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_aic PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_bic PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_loglikeobs PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_jac PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_summary_latex PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_distr PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_pvalues XFAIL [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_zstat PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_lnalpha PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_params PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_conf_int PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_predict PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1Newton::test_predict_xb PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_fit_regularized_invalid_method PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_cov_params SKIPPED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_llf PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_llnull PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_llr PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_llr_pvalue PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_normalized_cov_params XFAIL [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_dof PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_aic PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_bic PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_loglikeobs PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_jac PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_summary_latex PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_distr PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_pvalues XFAIL [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_bse PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_params PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_alpha PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_conf_int PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_zstat PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_fittedvalues PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_predict PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB2BFGS::test_predict_xb PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_fit_regularized_invalid_method PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_cov_params SKIPPED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_llnull PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_llr_pvalue PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_normalized_cov_params XFAIL [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_dof PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_loglikeobs PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_jac PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_summary_latex PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_distr PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_pvalues XFAIL [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_bse PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_aic PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_bic PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_llf PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_llr PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_zstat PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_lnalpha PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_params PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_conf_int PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_predict PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_predict_xb PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPNB1BFGS::test_init_kwds PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_params PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_cov_params PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_df PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_t_test PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_f_test PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPL1Compatability::test_bad_r_matrix PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPPredictProb::test_predict_prob_p1 PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialPPredictProb::test_predict_prob_p2 PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestPoissonNull::test_llnull PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB1Null::test_llnull PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNB2Null::test_llnull PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNBP2Null::test_llnull PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNBP2Null::test_start_null PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNBP1Null::test_llnull PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestNegativeBinomialNBP1Null::test_start_null PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::TestGeneralizedPoissonNull::test_llnull PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_null_options PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_optim_kwds_prelim PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_unchanging_degrees_of_freedom PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_mnlogit_float_name PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_cov_confint_pandas PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_discrete.py::test_mlogit_t_test PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_margins.py::TestPoissonMargin::test_margins_table PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_margins.py::TestPoissonMarginDummy::test_margins_table PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_margins.py::TestNegBinMargin::test_margins_table PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_margins.py::TestNegBinMarginDummy::test_margins_table PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_margins.py::TestNegBinPMargin::test_margins_table PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::TestNegativeBinomialPPredict::test_predict_linear PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::TestNegativeBinomialPPredict::test_score_test PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::TestNegativeBinomialPPredict::test_score_test_alpha PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::TestNegativeBinomialPPredict::test_influence PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::TestNegativeBinomialPPredict::test_basic PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::TestNegativeBinomialPPredict::test_predict PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::TestNegativeBinomialPPredict::test_diagnostic PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::TestZINegativeBinomialPPredict::test_basic PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::TestZINegativeBinomialPPredict::test_predict PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::TestZINegativeBinomialPPredict::test_diagnostic PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::TestGeneralizedPoissonPredict::test_predict_linear PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::TestGeneralizedPoissonPredict::test_score_test PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::TestGeneralizedPoissonPredict::test_score_test_alpha PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::TestGeneralizedPoissonPredict::test_influence PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::test_distr[case0] PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::test_distr[case1] PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::test_distr[case2] PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::test_distr[case3] PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::test_distr[case4] PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::test_distr[case5] PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::test_distr[case6] PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::test_distr[case7] PASSED [ 7%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::test_distr[case8] PASSED [ 8%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::test_distr[case9] PASSED [ 8%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::test_distr[case10] PASSED [ 8%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::test_distr[case11] PASSED [ 8%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::test_distr[case12] PASSED [ 8%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::test_distr[case13] PASSED [ 8%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_predict.py::test_distr[case14] PASSED [ 8%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonClu::test_basic PASSED [ 8%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonClu::test_oth PASSED [ 8%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonClu::test_ttest PASSED [ 8%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonClu::test_waldtest PASSED [ 8%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluGeneric::test_basic PASSED [ 8%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluGeneric::test_oth PASSED [ 8%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluGeneric::test_ttest PASSED [ 8%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonCluGeneric::test_waldtest PASSED [ 8%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Generic::test_basic PASSED [ 8%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Generic::test_oth PASSED [ 8%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/tests/test_sandwich_cov.py::TestPoissonHC1Generic::test_ttest PASSED [ 8%] 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../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestTweedieRepeatedvsAverage::test_pearson_chi2 PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestTweedieRepeatedvsAverage::test_getprediction PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsAverage::test_basic PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsAverage::test_residuals PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsAverage::test_compare_optimizers PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsAverage::test_pearson_chi2 PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsAverage::test_getprediction PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsDuplicated::test_basic PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsDuplicated::test_residuals PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsDuplicated::test_compare_optimizers PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsDuplicated::test_pearson_chi2 PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomial0RepeatedvsDuplicated::test_getprediction PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::test_warnings_raised PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::test_weights_different_formats[list] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::test_weights_different_formats[ndarray] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::test_weights_different_formats[Series] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomialVsVarWeights::test_basic PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomialVsVarWeights::test_residuals PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomialVsVarWeights::test_compare_optimizers PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomialVsVarWeights::test_pearson_chi2 PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestBinomialVsVarWeights::test_getprediction PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianWLS::test_basic PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianWLS::test_residuals PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianWLS::test_compare_optimizers PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianWLS::test_pearson_chi2 PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::TestGlmGaussianWLS::test_getprediction PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::test_incompatible_input PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_glm_weights.py::test_poisson_residuals PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct0-fam0] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct0-fam1] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct0-fam2] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct1-fam0] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct1-fam1] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct1-fam2] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct2-fam0] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct2-fam1] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_numdiff[cov_struct2-fam2] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct0-fam0] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct0-fam1] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct0-fam2] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct1-fam0] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct1-fam1] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct1-fam2] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct2-fam0] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct2-fam1] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_qif_fit[cov_struct2-fam2] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_formula[cov_struct0] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_formula[cov_struct1] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_qif.py::test_formula[cov_struct2] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_score_test.py::TestScoreTest::test_wald_score PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_score_test.py::TestScoreTest::test_dispersion PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_score_test.py::TestScoreTestDispersed::test_wald_score PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_score_test.py::TestScoreTestDispersed::test_dispersion PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_score_test.py::TestScoreTestPoisson::test_dispersion PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_score_test.py::TestScoreTestPoisson::test_wald_score PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_score_test.py::TestScoreTestPoissonDispersed::test_dispersion PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_score_test.py::TestScoreTestPoissonDispersed::test_wald_score PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/tests/test_score_test.py::TestScoreTestGaussian::test_wald_score PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_agreement.py::test_mean_diff_plot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_boxplots.py::test_violinplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_boxplots.py::test_violinplot_bw_factor PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_boxplots.py::test_beanplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_boxplots.py::test_beanplot_jitter PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_boxplots.py::test_beanplot_side_right PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_boxplots.py::test_beanplot_side_left PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_boxplots.py::test_beanplot_legend_text PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_correlation.py::test_plot_corr PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_correlation.py::test_plot_corr_grid PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_dotplot.py::test_all PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_plot_both PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_plot_rainbow PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_plot_pandas[str] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_plot_pandas[int] PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_formatting PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_formatting_errors PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_plottype PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_factorplots.py::TestInteractionPlot::test_recode_series PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_hdr_basic PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_hdr_basic_brute PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_hdr_plot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_hdr_alpha PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_hdr_multiple_alpha PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_hdr_threshold PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_hdr_bw PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_hdr_ncomp PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_banddepth_BD2 PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_banddepth_MBD PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_functional.py::test_fboxplot_rainbowplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyNoFit::test_qqplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyNoFit::test_ppplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyNoFit::test_probplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyNoFit::test_probplot_exceed PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyNoFit::test_qqplot_other_array PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyNoFit::test_ppplot_other_array PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyNoFit::test_probplot_other_array XFAIL [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyNoFit::test_qqplot_other_prbplt PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyNoFit::test_ppplot_other_prbplt PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyNoFit::test_probplot_other_prbplt XFAIL [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyNoFit::test_qqplot_custom_labels PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyNoFit::test_ppplot_custom_labels PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyNoFit::test_probplot_custom_labels PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyNoFit::test_qqplot_pltkwargs PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyNoFit::test_ppplot_pltkwargs PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyNoFit::test_probplot_pltkwargs PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyNoFit::test_fit_params PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyWithFit::test_qqplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyWithFit::test_ppplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyWithFit::test_probplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyWithFit::test_probplot_exceed PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyWithFit::test_qqplot_other_array PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyWithFit::test_ppplot_other_array PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyWithFit::test_probplot_other_array XFAIL [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyWithFit::test_qqplot_other_prbplt PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyWithFit::test_ppplot_other_prbplt PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyWithFit::test_probplot_other_prbplt XFAIL [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyWithFit::test_qqplot_custom_labels PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyWithFit::test_ppplot_custom_labels PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyWithFit::test_probplot_custom_labels PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyWithFit::test_qqplot_pltkwargs PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyWithFit::test_ppplot_pltkwargs PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyWithFit::test_probplot_pltkwargs PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotLongelyWithFit::test_fit_params PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_qqplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_ppplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_probplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_probplot_exceed PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_qqplot_other_array PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_ppplot_other_array PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_probplot_other_array XFAIL [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_qqplot_other_prbplt PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_ppplot_other_prbplt PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_probplot_other_prbplt XFAIL [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_qqplot_custom_labels PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_ppplot_custom_labels PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_probplot_custom_labels PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_qqplot_pltkwargs PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_ppplot_pltkwargs PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_probplot_pltkwargs PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalMinimal::test_fit_params PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_qqplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_ppplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_probplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_probplot_exceed PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_qqplot_other_array PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_ppplot_other_array PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_probplot_other_array XFAIL [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_qqplot_other_prbplt PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_ppplot_other_prbplt PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_probplot_other_prbplt XFAIL [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_qqplot_custom_labels PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_ppplot_custom_labels PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_probplot_custom_labels PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_qqplot_pltkwargs PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_ppplot_pltkwargs PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_probplot_pltkwargs PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalWithFit::test_fit_params PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_qqplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_ppplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_probplot PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_probplot_exceed PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_qqplot_other_array PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_ppplot_other_array PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_probplot_other_array XFAIL [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_qqplot_other_prbplt PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_ppplot_other_prbplt PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_probplot_other_prbplt XFAIL [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_qqplot_custom_labels PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_ppplot_custom_labels PASSED [ 15%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_probplot_custom_labels PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_qqplot_pltkwargs PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_ppplot_pltkwargs PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_probplot_pltkwargs PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_fit_params PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_loc_set PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_scale_set PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalFullDist::test_exceptions PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestCompareSamplesDifferentSize::test_qqplot PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestCompareSamplesDifferentSize::test_ppplot PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_qqplot PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_ppplot PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_probplot PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_probplot_exceed PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_qqplot_other_array PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_ppplot_other_array PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_probplot_other_array XFAIL [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_qqplot_other_prbplt PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_ppplot_other_prbplt PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_probplot_other_prbplt XFAIL [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_qqplot_custom_labels PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_ppplot_custom_labels PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_probplot_custom_labels PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_qqplot_pltkwargs PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_ppplot_pltkwargs PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_probplot_pltkwargs PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_fit_params PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_loc_set PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_scale_set PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_loc_set_in_dist PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestProbPlotRandomNormalLocScaleDist::test_scale_set_in_dist PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestTopLevel::test_qqplot PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestTopLevel::test_qqplot_pltkwargs PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestTopLevel::test_qqplot_2samples_prob_plot_objects PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestTopLevel::test_qqplot_2samples_arrays PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_invalid_dist_config PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_qqplot_unequal PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestCheckDist::test_good PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestCheckDist::test_bad PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestDoPlot::test_baseline PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestDoPlot::test_with_ax PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestDoPlot::test_plot_full_options PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestDoPlot::test_step_baseline PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestDoPlot::test_step_full_options PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestDoPlot::test_plot_qq_line PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestDoPlot::test_step_qq_line PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestQQLine::test_badline PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestQQLine::test_non45_no_x PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestQQLine::test_non45_no_y PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestQQLine::test_non45_no_x_no_y PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestQQLine::test_45 PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestQQLine::test_45_fmt PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestQQLine::test_45_fmt_lineoptions PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestQQLine::test_r PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestQQLine::test_r_fmt PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestQQLine::test_r_fmt_lineoptions PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestQQLine::test_s PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestQQLine::test_s_fmt PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestQQLine::test_s_fmt_lineoptions PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestQQLine::test_q PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestQQLine::test_q_fmt PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestQQLine::test_q_fmt_lineoptions PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestPlottingPosition::test_weibull PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestPlottingPosition::test_lininterp PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestPlottingPosition::test_piecewise PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestPlottingPosition::test_approx_med_unbiased PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::TestPlottingPosition::test_cunnane PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_param_unpacking PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[None-30-30-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[None-30-30-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[None-30-50-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[None-30-50-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[None-50-30-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[None-50-30-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[None-50-50-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[None-50-50-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[45-30-30-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[45-30-30-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[45-30-50-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[45-30-50-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[45-50-30-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[45-50-30-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[45-50-50-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[45-50-50-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[s-30-30-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[s-30-30-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[s-30-50-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[s-30-50-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[s-50-30-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[s-50-30-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[s-50-50-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[s-50-50-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[r-30-30-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[r-30-30-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[r-30-50-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[r-30-50-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[r-50-30-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[r-50-30-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[r-50-50-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[r-50-50-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[q-30-30-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[q-30-30-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[q-30-50-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[q-30-50-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[q-50-30-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[q-50-30-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[q-50-50-labels0] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_correct_labels[q-50-50-labels1] PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_gofplots.py::test_axis_order PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_data_conversion PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_mosaic_simple PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_mosaic PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_mosaic_very_complex PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_axes_labeling PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_mosaic_empty_cells PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_recursive_split PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test__reduce_dict PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test__key_splitting PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_proportion_normalization PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_false_split PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_rect_pure_split PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_rect_deformed_split PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_gap_split PASSED [ 16%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/graphics/tests/test_mosaicplot.py::test_default_arg_index 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../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_vectorized[case7] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_weights[case0] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_weights[case1] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_weights[case2] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_weights[case3] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_weights[case4] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_weights[case5] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_weights[case6] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsRplus::test_kernels_weights[case7] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsUnit::test_kernels[case0] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsUnit::test_kernels[case1] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsUnit::test_kernels_vectorized[case0] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsUnit::test_kernels_vectorized[case1] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsUnit::test_kernels_weights[case0] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_asymmetric.py::TestKernelsUnit::test_kernels_weights[case1] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_bandwidths.py::TestBandwidthCalculation::test_calculate_bandwidth_gaussian PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_bandwidths.py::TestBandwidthCalculation::test_calculate_normal_reference_bandwidth PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_bandwidths.py::TestEpanechnikov::test_calculate_normal_reference_constant PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_bandwidths.py::TestGaussian::test_calculate_normal_reference_constant PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_bandwidths.py::TestBiweight::test_calculate_normal_reference_constant PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_bandwidths.py::TestTriweight::test_calculate_normal_reference_constant PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_bandwidths.py::TestAllBandwidthZero::test_bandwidth_zero PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_bandwidths.py::TestAnyBandwidthZero::test_bandwidth_zero PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEExceptions::test_check_is_fit_exception PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEExceptions::test_non_weighted_fft_exception PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEExceptions::test_wrong_weight_length_exception PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEExceptions::test_non_gaussian_fft_exception PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_density PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_evaluate PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_support_gridded PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_cdf_gridded PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_sf_gridded PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGauss::test_icdf_gridded PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussPandas::test_density PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussPandas::test_evaluate PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussPandas::test_support_gridded PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussPandas::test_cdf_gridded PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussPandas::test_sf_gridded PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussPandas::test_icdf_gridded PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEEpanechnikov::test_density PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEEpanechnikov::test_evaluate PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDETriangular::test_density PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDETriangular::test_evaluate PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEBiweight::test_density PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEBiweight::test_evaluate PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKdeWeights::test_density PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKdeWeights::test_evaluate PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussFFT::test_density PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEGaussFFT::test_evaluate PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWGauss::test_density XFAIL [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWGauss::test_evaluate PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWGauss::test_compare PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWGauss::test_kernel_constants PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWEpa::test_density XFAIL [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWEpa::test_evaluate PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWEpa::test_compare PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWEpa::test_kernel_constants PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWTri::test_density XFAIL [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWTri::test_evaluate PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWTri::test_compare PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWTri::test_kernel_constants PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWBiw::test_density XFAIL [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWBiw::test_evaluate PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWBiw::test_compare PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWBiw::test_kernel_constants PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos::test_density XFAIL [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos::test_evaluate SKIPPED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos::test_compare PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos::test_kernel_constants PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos2::test_density XFAIL [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos2::test_evaluate PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos2::test_compare PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDEWCos2::test_kernel_constants PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestNormConstant::test_norm_constant_calculation PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::test_kde_bw_positive PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::test_fit_self PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDECustomBandwidth::test_check_is_fit_ok_with_custom_bandwidth PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDECustomBandwidth::test_check_is_fit_ok_with_standard_custom_bandwidth PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDECustomBandwidth::test_check_is_fit_ok_with_float_bandwidth[True] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kde.py::TestKDECustomBandwidth::test_check_is_fit_ok_with_float_bandwidth[False] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEUnivariate::test_pdf_non_fft PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEUnivariate::test_weighted_pdf_non_fft PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEUnivariate::test_all_samples_same_location_bw PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEUnivariate::test_int PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_pdf_mixeddata_CV_LS PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_pdf_mixeddata_LS_vs_ML PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_pdf_mixeddata_CV_ML PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_pdf_continuous PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_pdf_ordered PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_unordered_CV_LS PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_continuous_cdf PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_mixeddata_cdf PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_continuous_cvls_efficient PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_continuous_cvml_efficient PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_efficient_notrandom PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariate::test_efficient_user_specified_bw PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_mixeddata_CV_LS PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_continuous_CV_ML PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_unordered_CV_LS PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_pdf_continuous PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_pdf_mixeddata PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_continuous_normal_ref PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_continuous_cdf PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_mixeddata_cdf PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_continuous_cvml_efficient PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_efficient_user_specified_bw PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::test_all_kernels[biw] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::test_all_kernels[cos] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::test_all_kernels[epa] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::test_all_kernels[gau] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::test_all_kernels[tri] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::test_all_kernels[triw] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_density.py::test_all_kernels[uni] PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_ordered_lc_cvls PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_continuousdata_lc_cvls PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_continuousdata_ll_cvls PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_continuous_mfx_ll_cvls PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_mixed_mfx_ll_cvls PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_mfx_nonlinear_ll_cvls XFAIL [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_continuous_cvls_efficient PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_censored_ll_cvls PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_continuous_lc_aic PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_significance_continuous PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_significance_discrete PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_user_specified_kernel PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_censored_user_specified_kernel PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_efficient_user_specificed_bw PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_censored_efficient_user_specificed_bw PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::test_invalid_bw PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernel_regression.py::test_invalid_kernel PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestEpan::test_smoothconf PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestEpan::test_smoothconf_data PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestGau::test_smoothconf PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestGau::test_smoothconf_data PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestUniform::test_smoothconf PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestUniform::test_smoothconf_data PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestTriangular::test_smoothconf PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestTriangular::test_smoothconf_data PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestCosine::test_smoothconf_data PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestCosine::test_smoothconf XFAIL [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestBiweight::test_smoothconf PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::TestBiweight::test_smoothconf_data PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_kernels.py::test_tricube PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_import PASSED [ 18%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_flat[False] PASSED [ 19%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_flat[True] PASSED [ 19%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_range PASSED [ 19%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/tests/test_lowess.py::TestLowess::test_simple PASSED [ 19%] 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../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_residuals PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_degrees PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_bcov_unscaled PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_bcov_scaled PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_tvalues PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::TestRlmSresid::test_tpvalues PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_missing PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_rlm_start_values PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_rlm_start_values_errors PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_fit[AndrewWave] PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_const[AndrewWave] PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_fit[LeastSquares] PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_const[LeastSquares] PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_fit[HuberT] PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_const[HuberT] PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_fit[TrimmedMean] PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_const[TrimmedMean] PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_fit[TukeyBiweight] PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_const[TukeyBiweight] PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_fit[Hampel] PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_const[Hampel] PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_fit[RamsayE] PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_perfect_const[RamsayE] PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_alt_criterion[weights] PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_alt_criterion[coefs] PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_alt_criterion[sresid] PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_rlm.py::test_bad_criterion PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestChem::test_mean PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestChem::test_median PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestChem::test_mad PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestChem::test_iqr PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestChem::test_qn PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestChem::test_huber_scale PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestChem::test_huber_location PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestChem::test_huber_huberT PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestChem::test_huber_Hampel PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestMad::test_mad PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestMad::test_mad_empty PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestMad::test_mad_center PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestMadAxes::test_axis0 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestMadAxes::test_axis1 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestMadAxes::test_axis2 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestMadAxes::test_axisneg1 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestIqr::test_iqr PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestIqr::test_iqr_empty PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestIqrAxes::test_axis0 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestIqrAxes::test_axis1 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestIqrAxes::test_axis2 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestIqrAxes::test_axisneg1 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestQn::test_qn_naive PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestQn::test_qn_robustbase PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestQn::test_qn_empty PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestQnAxes::test_axis0 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestQnAxes::test_axis1 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestQnAxes::test_axis2 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestQnAxes::test_axisneg1 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestHuber::test_huber_result_shape PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestHuberAxes::test_default PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestHuberAxes::test_axis1 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestHuberAxes::test_axis2 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::TestHuberAxes::test_axisneg1 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/tests/test_scale.py::test_mad_axis_none PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_extras.py::test_skewnorm PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_extras.py::test_skewt PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_gof_new.py::test_loop_vectorized_batch_equivalence PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_multivariate.py::Test_MVN_MVT_prob::test_mvn_mvt_1 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_multivariate.py::Test_MVN_MVT_prob::test_mvn_mvt_2 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_multivariate.py::Test_MVN_MVT_prob::test_mvn_mvt_3 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_multivariate.py::Test_MVN_MVT_prob::test_mvn_mvt_4 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_multivariate.py::Test_MVN_MVT_prob::test_mvn_mvt_5 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_multivariate.py::TestMVDistributions::test_mvn_pdf PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_multivariate.py::TestMVDistributions::test_mvt_pdf PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_norm_expan.py::TestExpandNormMom::test_dist1 PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_norm_expan.py::TestExpandNormMom::test_cdf_ppf_roundtrip PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_norm_expan.py::TestExpandNormMom::test_pdf PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_norm_expan.py::TestExpandNormMom::test_mvsk PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_norm_expan.py::TestExpandNormSample::test_ks PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_norm_expan.py::TestExpandNormSample::test_mvsk PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_transf.py::Test_Transf2::test_equivalent PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/distributions/tests/test_transf.py::Test_Transf2::test_equivalent_negsq PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_kernel_extras.py::TestSemiLinear::test_basic PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother1::test_predict PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother1::test_coef PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother1::test_df PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother2::test_predict PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother2::test_coef PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother2::test_df PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother3::test_predict PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother3::test_coef PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/nonparametric/tests/test_smoothers.py::TestPolySmoother3::test_df PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/panel/tests/test_random_panel.py::test_short_panel PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::test_iv2sls_r PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::test_ivgmm0_r PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::test_ivgmm1_stata PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMOLS::test_basic PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMOLS::test_other XFAIL [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt1::test_basic PASSED [ 26%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt1::test_other PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt1::test_hypothesis PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt1::test_summary PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt1::test_use_t PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostep::test_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostep::test_other PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostep::test_hypothesis PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostep::test_summary PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostep::test_use_t PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostepNO::test_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostepNO::test_other PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostepNO::test_hypothesis PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostepNO::test_summary PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStTwostepNO::test_use_t PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_hypothesis PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_summary PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_use_t PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_bse_other PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestep::test_other XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestepNO::test_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestepNO::test_hypothesis PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestepNO::test_summary PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestepNO::test_use_t PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOnestepNO::test_other XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_hypothesis PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_summary PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_use_t PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_other XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiter::test_bse_other PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO::test_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO::test_hypothesis PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO::test_summary PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO::test_use_t PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO::test_other XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Linear::test_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Linear::test_hypothesis PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Linear::test_summary PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Linear::test_use_t PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Linear::test_other XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_hypothesis PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_summary PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_use_t PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_other XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterNO_Nonlinear::test_score PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterOLS_Linear::test_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterOLS_Linear::test_hypothesis PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterOLS_Linear::test_summary PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterOLS_Linear::test_use_t PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMStOneiterOLS_Linear::test_other XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestGMMSt2::test_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_other PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_hypothesis PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_hausman PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_summary PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::TestIV2SLSSt1::test_input_dimensions PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::test_noconstant PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm.py::test_gmm_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddOnestep::test_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddOnestep::test_other PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddOnestep::test_summary PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddTwostep::test_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddTwostep::test_other PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMAddTwostep::test_summary PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultOnestep::test_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultOnestep::test_other PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultOnestep::test_summary PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostep::test_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostep::test_other PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostep::test_summary PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepDefault::test_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepDefault::test_other PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepDefault::test_summary PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepCenter::test_basic PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepCenter::test_other PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepCenter::test_summary PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/regression/tests/test_gmm_poisson.py::TestGMMMultTwostepCenter::test_more PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/stats/tests/test_multicomp.py::test_tukey_pvalues PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/stats/tests/test_runs.py::test_mean_cutoff PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/stats/tests/test_runs.py::test_median_cutoff PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/stats/tests/test_runs.py::test_numeric_cutoff PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestAdditiveModel::test_predict PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestAdditiveModel::test_params PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestAdditiveModel::test_df XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestAdditiveModel::test_fitted PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMPoisson::test_predict PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMPoisson::test_fitted XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMPoisson::test_params PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMPoisson::test_df XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMPoisson::test_mu PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMPoisson::test_prediction PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMBinomial::test_predict PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMBinomial::test_fitted XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMBinomial::test_params PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMBinomial::test_df XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMBinomial::test_mu PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMBinomial::test_prediction PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGaussianLogLink::test_predict XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGaussianLogLink::test_fitted XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGaussianLogLink::test_params XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGaussianLogLink::test_df XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGaussianLogLink::test_mu XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGaussianLogLink::test_prediction XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGamma::test_predict PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGamma::test_fitted XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGamma::test_params PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGamma::test_df XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGamma::test_mu PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMGamma::test_prediction PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMNegativeBinomial::test_predict XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMNegativeBinomial::test_params XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMNegativeBinomial::test_mu XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMNegativeBinomial::test_prediction XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMNegativeBinomial::test_fitted XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_gam.py::TestGAMNegativeBinomial::test_df XFAIL [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_pca.py::test_pca_princomp PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_pca.py::test_pca_svd PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_predict_functional.py::TestPredFunc::test_formula PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_predict_functional.py::TestPredFunc::test_lm_contrast PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_predict_functional.py::TestPredFunc::test_glm_formula_contrast PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_predict_functional.py::TestPredFunc::test_scb PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_predict_functional.py::TestPredFunc::test_glm_formula PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/tests/test_predict_functional.py::TestPredFunc::test_noformula_prediction PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_scalar PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_vector PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_invalid_parameters PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_handful_to_tbl PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_all_to_tbl SKIPPED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_handful_to_ch PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestQsturng::test_10000_to_ch PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_scalar PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_vector PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_v_equal_one PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_invalid_parameters PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_handful_to_known_values PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/libqsturng/tests/test_qsturng.py::TestPsturng::test_100_random_values PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnovaLM::test_results PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnovaLMNoconstant::test_results PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnovaLMCompare::test_results PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnovaLMCompareNoconstant::test_results PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova2::test_results PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova2Noconstant::test_results PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova2HC0::test_results PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova2HC1::test_results PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova2HC2::test_results PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova2HC3::test_results PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova3::test_results PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova3HC0::test_results PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova3HC1::test_results PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova3HC2::test_results PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova.py::TestAnova3HC3::test_results PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_single_factor_repeated_measures_anova PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_two_factors_repeated_measures_anova PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_three_factors_repeated_measures_anova PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_repeated_measures_invalid_factor_name PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_repeated_measures_collinearity PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_repeated_measures_unbalanced_data PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_repeated_measures_aggregation PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_repeated_measures_aggregation_one_subject_duplicated PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_repeated_measures_aggregate_func PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_repeated_measures_aggregate_func_mean PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_anova_rm.py::test_repeated_measures_aggregate_compare_with_ezANOVA PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_base.py::test_holdertuple PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_base.py::test_holdertuple2 PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_homogeneity PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_SquareTable_from_data PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_SquareTable_nonsquare PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_cumulative_odds PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_local_odds PASSED [ 27%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/tests/test_contingency_tables.py::test_shifting 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../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py::test_nonstationary_series PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py::test_nonstationary_series_variance XFAIL [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py::test_invalid PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_durbin_levinson.py::test_misc PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_brockwell_davis_example_661 PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_brockwell_davis_example_662 PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_integrated PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_integrated_invalid PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_results PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_iterations PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_misc PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_alternate_arma_estimators_valid PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_alternate_arma_estimators_invalid PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_gls.py::test_arma_kwargs PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_brockwell_davis_example_517 PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_itsmr PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_initial_order XFAIL [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_invalid_orders XFAIL [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_nonconsecutive_lags PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_unbiased_error PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_set_default_unbiased PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[2-ma_order0-None-None] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[ar_order1-0-fixed_params1-None] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[1-3-fixed_params2-invalid_fixed_params2] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[ar_order3-ma_order3-fixed_params3-invalid_fixed_params3] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[0-0-fixed_params4-invalid_fixed_params4] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[5-ma_order5-fixed_params5-invalid_fixed_params5] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[0-2-fixed_params6-None] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[1-0-fixed_params7-None] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[ar_order8-3-fixed_params8-None] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_validate_fixed_params[2-2-fixed_params9-None] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_package_fixed_and_free_params_info[fixed_params0-spec_ar_lags0-spec_ma_lags0-expected_bunch0] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_package_fixed_and_free_params_info[fixed_params1-spec_ar_lags1-spec_ma_lags1-expected_bunch1] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_package_fixed_and_free_params_info[fixed_params2-spec_ar_lags2-spec_ma_lags2-expected_bunch2] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_stitch_fixed_and_free_params[fixed_lags0-free_lags0-fixed_params0-free_params0-spec_lags0-expected_all_params0] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_stitch_fixed_and_free_params[fixed_lags1-free_lags1-fixed_params1-free_params1-spec_lags1-expected_all_params1] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_stitch_fixed_and_free_params[fixed_lags2-free_lags2-fixed_params2-free_params2-spec_lags2-expected_all_params2] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_stitch_fixed_and_free_params[fixed_lags3-free_lags3-fixed_params3-free_params3-spec_lags3-expected_all_params3] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_stitch_fixed_and_free_params[fixed_lags4-free_lags4-fixed_params4-free_params4-spec_lags4-expected_all_params4] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_stitch_fixed_and_free_params[fixed_lags5-free_lags5-fixed_params5-free_params5-spec_lags5-expected_all_params5] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_stitch_fixed_and_free_params[fixed_lags6-free_lags6-fixed_params6-free_params6-spec_lags6-expected_all_params6] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_stitch_fixed_and_free_params[fixed_lags7-free_lags7-fixed_params7-free_params7-spec_lags7-expected_all_params7] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_itsmr_with_fixed_params[fixed_params0] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_itsmr_with_fixed_params[fixed_params1] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_itsmr_with_fixed_params[fixed_params2] PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_unbiased_error_with_fixed_params PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_hannan_rissanen.py::test_set_default_unbiased_with_fixed_params PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_brockwell_davis_example_515 PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_ma_itsmr PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_ma_invalid PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_brockwell_davis_example_524 PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_brockwell_davis_example_524_variance XFAIL [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_brockwell_davis_example_525 PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_brockwell_davis_example_541 PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_statespace PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_statespace_seasonal PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_statespace_nonconsecutive PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_integrated PASSED [ 47%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_misc PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_innovations.py::test_innovations_mle_invalid PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_statespace.py::test_basic PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_statespace.py::test_start_params PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_yule_walker.py::test_brockwell_davis_example_511 PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_yule_walker.py::test_brockwell_davis_example_514 PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_yule_walker.py::test_itsmr PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_yule_walker.py::test_invalid PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/estimators/tests/test_yule_walker.py::test_invalid_xfail XFAIL [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_default_trend PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_invalid PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_yule_walker PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_burg PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_hannan_rissanen PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_innovations PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_innovations_mle PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_statespace PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_low_memory PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_clone PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_constant_integrated_model_error PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_forecast PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_forecast_with_exog PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_append PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_append_with_exog PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_append_with_exog_and_trend PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_append_with_exog_pandas PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_cov_type_none PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_nonstationary_gls_error PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_hannan_rissanen_with_fixed_params[1-1-fixed_params0] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_hannan_rissanen_with_fixed_params[1-1-fixed_params1] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_hannan_rissanen_with_fixed_params[2-3-fixed_params2] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_hannan_rissanen_with_fixed_params[ar_order3-0-fixed_params3] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_hannan_rissanen_with_fixed_params[ar_order4-ma_order4-fixed_params4] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_reproducible_simulation[7] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_reproducible_simulation[RandomState] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_model.py::test_reproducible_simulation[default_rng] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_init PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_set_params_single PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_set_params_single_nonconsecutive PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_set_params_multiple PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_set_poly_short_lags PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_set_poly_short_lags_nonconsecutive PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_set_poly_longer_lags PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_is_stationary PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_is_invertible PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_is_valid PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_params.py::test_repr_str PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-0-0-0-params0-p] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-0-0-0-params1-p] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-0-0-0-params2-p] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[2-0-0-0-params3-p] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[20-0-0-0-params4-p] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-1-0-0-params5-p] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-1-1-4-params6-p] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-1-0-0-params7-p] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-1-1-4-params8-p] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-0-0-0-params9-q] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-0-0-0-params10-q] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-0-0-0-params11-q] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[2-0-0-0-params12-q] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[20-0-0-0-params13-q] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-1-0-0-params14-q] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[0-1-1-4-params15-q] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-1-0-0-params16-q] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification_ar_or_ma[1-1-1-4-params17-q] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-0-0-0-0-0-0-0-True-True-False] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-1-0-1-0-0-0-0-True-True-False] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-1-1-1-0-0-0-0-True-True-False] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-1-0-0-0-0-0-4-True-True-False] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-0-0-0-1-1-1-4-True-True-False] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-1-0-0-1-0-0-4-True-True-False] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-1-0-0-1-1-1-4-True-True-False] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-2-1-3-4-1-3-12-True-True-False] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-p8-0-0-1-0-0-4-True-True-False] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-0-0-0-0-0-Q9-4-True-True-False] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-p10-0-q10-P10-0-Q10-4-True-True-False] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-2-1-3-4-1-3-12-False-False-True] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-2-1-3-4-1-3-12-True-False-True] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-None-2-1-3-4-1-3-12-False-True-True] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[True-None-2-1-3-4-1-3-12-False-True-True] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-2-2-1-3-4-1-3-12-False-True-True] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[True-2-2-1-3-4-1-3-12-False-True-True] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[y-None-2-1-3-4-1-3-12-False-True-True] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[None-exog18-2-1-3-4-1-3-12-False-True-True] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[y-exog19-2-1-3-4-1-3-12-False-True-True] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[y-exog20-2-1-3-4-1-3-12-False-True-True] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[True-exog21-2-1-3-4-1-3-12-False-True-True] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_specification[y-2-2-1-3-4-1-3-12-False-True-True] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_misc PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_invalid PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order0-seasonal_order0-None-None-None-valid0] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order1-seasonal_order1-None-None-None-valid1] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order2-seasonal_order2-None-None-None-valid2] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order3-seasonal_order3-None-None-None-valid3] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order4-seasonal_order4-None-None-None-valid4] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order5-seasonal_order5-True-None-None-valid5] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order6-seasonal_order6-False-None-None-valid6] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/arima/tests/test_specification.py::test_valid_estimators[order7-seasonal_order7-None-True-None-valid7] PASSED [ 48%] 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48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::test_cfitz_pandas PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::test_hpfilter_pandas PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_convolution PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_convolution2d PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_recursive PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_pandas PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_pandas2d PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::TestFilters::test_odd_length_filter PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/filters/tests/test_filters.py::test_pandas_freq_decorator PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_stl.py::test_smoke PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_stl.py::test_sharex PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_stl.py::test_equivalence_forecast[1-ETSModel] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_stl.py::test_equivalence_forecast[7-ETSModel] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_stl.py::test_equivalence_forecast[23-ETSModel] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_stl.py::test_exceptions PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_stl.py::test_get_prediction PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_stl.py::test_no_var_pred[True] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_stl.py::test_no_var_pred[False] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-True-True-None] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-True-True-4] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-True-True-12] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-True-False-None] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-True-False-4] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-True-False-12] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-False-True-None] PASSED [ 48%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: array, exponential: True-auto-True-True-False-True-4] PASSED [ 48%] 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../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-True-True-4] PASSED [ 53%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-True-True-12] PASSED [ 53%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-True-False-None] PASSED [ 53%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-True-False-4] PASSED [ 53%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-True-False-12] PASSED [ 53%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-False-True-None] PASSED [ 53%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-False-True-4] PASSED [ 53%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-False-True-12] PASSED [ 53%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-False-False-None] PASSED [ 53%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/forecasting/tests/test_theta.py::test_smoke[type: series, exponential: False-multiplicative-False-False-False-False-4] PASSED [ 53%] 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PASSED [ 54%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_equivalence_cython_python[add-None] PASSED [ 54%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_equivalence_cython_python[mul-add] PASSED [ 54%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_equivalence_cython_python[mul-mul] PASSED [ 54%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_equivalence_cython_python[mul-None] PASSED [ 54%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_equivalence_cython_python[None-add] PASSED [ 54%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/holtwinters/tests/test_holtwinters.py::test_equivalence_cython_python[None-mul] PASSED [ 54%] 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../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[1-6-1-True] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[3-6-1-True] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[1-1-1-False] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[3-1-1-False] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[1-6-1-False] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[3-6-1-False] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[k_factors8-factor_orders8-1-True] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[k_factors9-factor_orders9-1-False] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[k_factors10-factor_orders10-factor_multiplicities10-True] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_missing[k_factors11-factor_orders11-factor_multiplicities11-False] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[1-1-1-True] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[3-1-1-True] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[1-6-1-True] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[3-factor_orders3-1-True] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[1-1-1-False] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[3-1-1-False] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[1-6-1-False] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[3-factor_orders7-1-False] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[k_factors8-factor_orders8-1-True] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[k_factors9-factor_orders9-1-False] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[k_factors10-factor_orders10-factor_multiplicities10-True] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_emstep_methods_nonmissing[k_factors11-factor_orders11-factor_multiplicities11-False] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_news[news_112] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_news[news_222] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_news[news_block_112] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_frbny_nowcast.py::test_news[news_block_222] PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py::test_k_factor1 SKIPPED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py::test_em_nonstationary PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py::test_k_factor1_factor_order_6 PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py::test_k_factor2_factor_order_6 SKIPPED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py::test_two_blocks_factor_orders_6 SKIPPED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLevelAnalytic::test_results PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLevelAnalyticDirect::test_results PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLinearTrendAnalytic::test_results PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLinearTrendAnalyticDirect::test_results PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestLocalLinearTrendAnalyticMissing::test_results PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::test_common_level_analytic PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::test_common_level_restricted_analytic PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_forecasts PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_forecasts_error PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_forecasts_error_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_filtered_state PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_filtered_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_predicted_state PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_predicted_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_kalman_gain PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_loglike PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_state PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_state_autocov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_measurement_disturbance PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_measurement_disturbance_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_state_disturbance PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothed_state_disturbance_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_smoothing_error SKIPPED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_scaled_smoothed_estimator PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_scaled_smoothed_estimator_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_forecasts_error_diffuse_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_predicted_diffuse_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_scaled_smoothed_diffuse_estimator PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_simulation_smoothed_state XFAIL [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_simulation_smoothed_measurement_disturbance XFAIL [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_nobs_diffuse PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_initialization PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_Approx::test_initialization_approx PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_forecasts PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_forecasts_error PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_forecasts_error_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_filtered_state PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_filtered_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_predicted_state PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_predicted_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_kalman_gain PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_loglike PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_state PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_state_autocov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_measurement_disturbance PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_measurement_disturbance_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_state_disturbance PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothed_state_disturbance_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_smoothing_error SKIPPED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_scaled_smoothed_estimator PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_scaled_smoothed_estimator_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_forecasts_error_diffuse_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_predicted_diffuse_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_scaled_smoothed_diffuse_estimator PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_simulation_smoothed_state XFAIL [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_simulation_smoothed_measurement_disturbance XFAIL [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_simulation_smoothed_state_disturbance XFAIL [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_nobs_diffuse PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1_KFAS::test_initialization PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_forecasts PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_forecasts_error PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_forecasts_error_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_filtered_state PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_filtered_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_predicted_state PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_predicted_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_kalman_gain PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_loglike PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_state PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_state_autocov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_measurement_disturbance PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_state_disturbance PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_state_disturbance_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothing_error SKIPPED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_scaled_smoothed_estimator PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_scaled_smoothed_estimator_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_forecasts_error_diffuse_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_predicted_diffuse_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_scaled_smoothed_diffuse_estimator PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_simulation_smoothed_state XFAIL [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_simulation_smoothed_measurement_disturbance XFAIL [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_nobs_diffuse PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_initialization PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_initialization_approx PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_Approx::test_smoothed_measurement_disturbance_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_forecasts PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_forecasts_error PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_forecasts_error_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_filtered_state PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_filtered_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_predicted_state PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_predicted_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_kalman_gain PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_loglike PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_state PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_state_autocov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_measurement_disturbance PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_measurement_disturbance_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_state_disturbance PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothed_state_disturbance_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_smoothing_error SKIPPED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_scaled_smoothed_estimator PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_scaled_smoothed_estimator_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_forecasts_error_diffuse_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_predicted_diffuse_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_scaled_smoothed_diffuse_estimator PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_simulation_smoothed_state XFAIL [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_simulation_smoothed_measurement_disturbance XFAIL [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_simulation_smoothed_state_disturbance XFAIL [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_nobs_diffuse PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1MeasurementError_KFAS::test_initialization PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_forecasts PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_forecasts_error PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_forecasts_error_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_filtered_state PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_filtered_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_predicted_state PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_predicted_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_kalman_gain PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_loglike PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_state PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_state_autocov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_measurement_disturbance PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_measurement_disturbance_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_state_disturbance PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_state_disturbance_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothing_error SKIPPED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_scaled_smoothed_estimator PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_scaled_smoothed_estimator_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_forecasts_error_diffuse_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_predicted_diffuse_state_cov PASSED [ 59%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_scaled_smoothed_diffuse_estimator PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_simulation_smoothed_state XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_simulation_smoothed_measurement_disturbance XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_initialization PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_nobs_diffuse PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_initialization_approx PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_Approx::test_smoothed_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_forecasts PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_forecasts_error PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_filtered_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_filtered_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_predicted_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_predicted_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_kalman_gain PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_loglike PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_state_autocov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_measurement_disturbance PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_measurement_disturbance_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_state_disturbance PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothed_state_disturbance_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_smoothing_error SKIPPED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_scaled_smoothed_estimator PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_scaled_smoothed_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_forecasts_error_diffuse_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_predicted_diffuse_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_scaled_smoothed_diffuse_estimator PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_simulation_smoothed_state XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_simulation_smoothed_measurement_disturbance XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_simulation_smoothed_state_disturbance XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_initialization PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_nobs_diffuse PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Missing_KFAS::test_forecasts_error_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_forecasts PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_forecasts_error PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_forecasts_error_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_filtered_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_filtered_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_predicted_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_predicted_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_kalman_gain PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_loglike PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_state_autocov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_measurement_disturbance PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_measurement_disturbance_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_state_disturbance PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothed_state_disturbance_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_smoothing_error SKIPPED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_scaled_smoothed_estimator PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_scaled_smoothed_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_forecasts_error_diffuse_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_predicted_diffuse_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_scaled_smoothed_diffuse_estimator PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_simulation_smoothed_state XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_simulation_smoothed_measurement_disturbance XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_nobs_diffuse PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_initialization PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_Approx::test_initialization_approx PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_forecasts PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_forecasts_error PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_forecasts_error_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_filtered_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_predicted_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_kalman_gain PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_loglike PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_state_autocov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_measurement_disturbance PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_measurement_disturbance_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_state_disturbance PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_state_disturbance_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothing_error SKIPPED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_scaled_smoothed_estimator PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_scaled_smoothed_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_forecasts_error_diffuse_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_predicted_diffuse_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_scaled_smoothed_diffuse_estimator PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_simulation_smoothed_state XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_simulation_smoothed_measurement_disturbance XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_simulation_smoothed_state_disturbance XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_nobs_diffuse PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_initialization PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_predicted_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_filtered_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestVAR1Mixed_KFAS::test_smoothed_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_forecasts PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_forecasts_error PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_forecasts_error_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_filtered_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_filtered_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_predicted_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_predicted_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_kalman_gain PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_loglike PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_state_autocov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_measurement_disturbance PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_measurement_disturbance_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_state_disturbance PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothed_state_disturbance_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_smoothing_error SKIPPED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_scaled_smoothed_estimator PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_scaled_smoothed_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_forecasts_error_diffuse_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_predicted_diffuse_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_scaled_smoothed_diffuse_estimator PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_simulation_smoothed_state XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_simulation_smoothed_measurement_disturbance XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_nobs_diffuse PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_initialization PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_Approx::test_initialization_approx PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_forecasts PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_forecasts_error PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_forecasts_error_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_filtered_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_predicted_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_kalman_gain PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_loglike PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_state_autocov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_measurement_disturbance PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_measurement_disturbance_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_state_disturbance PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_state_disturbance_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothing_error SKIPPED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_scaled_smoothed_estimator PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_scaled_smoothed_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_forecasts_error_diffuse_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_predicted_diffuse_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_scaled_smoothed_diffuse_estimator PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_simulation_smoothed_state XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_simulation_smoothed_measurement_disturbance XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_simulation_smoothed_state_disturbance XFAIL [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_nobs_diffuse PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_initialization PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_predicted_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_filtered_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFM_KFAS::test_smoothed_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_forecasts PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_forecasts_error PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_forecasts_error_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_filtered_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_filtered_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_predicted_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_predicted_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_kalman_gain PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_loglike PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothed_state PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothed_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothed_state_autocov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothed_measurement_disturbance PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothed_measurement_disturbance_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothed_state_disturbance PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothed_state_disturbance_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_smoothing_error SKIPPED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_scaled_smoothed_estimator PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_scaled_smoothed_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_forecasts_error_diffuse_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_predicted_diffuse_state_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_scaled_smoothed_diffuse_estimator PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_scaled_smoothed_diffuse1_estimator_cov PASSED [ 60%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_scaled_smoothed_diffuse2_estimator_cov PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_simulation_smoothed_state XFAIL [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_simulation_smoothed_measurement_disturbance XFAIL [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_simulation_smoothed_state_disturbance XFAIL [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_nobs_diffuse PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_initialization PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::TestDFMCollapsed_Approx::test_initialization_approx PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::test_irrelevant_state XFAIL [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exact_diffuse_filtering.py::test_nondiagonal_obs_cov PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_fitted PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_output PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_forecasts PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_conf_int PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_initial_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed02::test_misc PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_fitted PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_output PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_forecasts PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_conf_int PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_initial_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPFixed06::test_misc PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPEstimated::test_fitted PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPEstimated::test_output PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPEstimated::test_forecasts PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPEstimated::test_conf_int PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPEstimated::test_initial_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPEstimated::test_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESFPPEstimated::test_misc PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESETSEstimated::test_fitted PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESETSEstimated::test_output PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESETSEstimated::test_forecasts PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESETSEstimated::test_conf_int PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESETSEstimated::test_initial_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESETSEstimated::test_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESETSEstimated::test_misc PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestSESETSEstimated::test_mle_estimates PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_fitted PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_output PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_forecasts PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_initial_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_misc PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltFPPFixed::test_conf_int PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_fitted PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_output PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_forecasts PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_conf_int PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_initial_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedFPPEstimated::test_misc PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedETSEstimated::test_fitted PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedETSEstimated::test_output PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedETSEstimated::test_forecasts PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedETSEstimated::test_conf_int PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedETSEstimated::test_initial_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedETSEstimated::test_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedETSEstimated::test_misc PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltDampedETSEstimated::test_mle_estimates PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_fitted PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_output PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_forecasts PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_conf_int PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_initial_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersFPPEstimated::test_misc PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersETSEstimated::test_fitted PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersETSEstimated::test_output PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersETSEstimated::test_forecasts PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersETSEstimated::test_conf_int PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersETSEstimated::test_initial_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersETSEstimated::test_states PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersETSEstimated::test_misc PASSED [ 61%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/tests/test_exponential_smoothing.py::TestHoltWintersDampedETSEstimated::test_fitted PASSED [ 61%] 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../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 73%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 74%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 0, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 75%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 76%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 77%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: 3, Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 78%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 79%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 80%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [1, 3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 81%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: True, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-bse] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-llf] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-scale] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-bse] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-cov_params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_model] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-df_resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-llf] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-nobs] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-scale] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-tvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0-use_t] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: n, Exog: None, Cov Type: HC0] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-params] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: nonrobust] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-bse] PASSED [ 82%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_model] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-llf] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-nobs] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-scale] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0-use_t] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: n, Exog: 2, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-bse] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-llf] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-scale] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-bse] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-cov_params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_model] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-df_resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-llf] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-nobs] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-scale] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-tvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0-use_t] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: c, Exog: None, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-bse] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_model] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-llf] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-nobs] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-scale] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0-use_t] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: c, Exog: 2, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-bse] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-llf] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-scale] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-bse] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-cov_params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_model] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-df_resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-llf] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-nobs] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-scale] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-tvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0-use_t] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: t, Exog: None, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-bse] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_model] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-llf] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-nobs] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-scale] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0-use_t] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: t, Exog: 2, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-bse] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-cov_params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_model] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-df_resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-fittedvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-llf] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-nobs] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-scale] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-tvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust-use_t] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: nonrobust] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-bse] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-cov_params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_model] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-df_resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-fittedvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-llf] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-nobs] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-scale] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-tvalues] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0-use_t] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: ct, Exog: None, Cov Type: HC0] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-bse] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-cov_params] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_model] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-df_resid] PASSED [ 83%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-fittedvalues] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-llf] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-nobs] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-params] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-resid] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-scale] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-tvalues] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust-use_t] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: nonrobust] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-bse] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-cov_params] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_model] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-df_resid] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-fittedvalues] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-llf] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-nobs] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-params] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-resid] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-scale] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-tvalues] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0-use_t] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_conf_int_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_f_test_ols_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_other_tests_autoreg[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply[AR: [3], Seasonal: False, Trend: ct, Exog: 2, Cov Type: HC0] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back: None] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back: 12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back: None] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back: 12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back: None] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back: 12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back: None] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back: 12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back: None] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back: 12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back: None] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back: 12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back: None] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_smoke_plots[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back: 12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 84%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 85%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 0, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 86%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 87%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 88%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 1, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 89%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 90%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: 3, trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 91%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: n, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: c, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 92%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: t, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: True, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 0, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: None, missing: drop, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: none, pandas: False, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: True, hold_back12] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 93%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_backNone] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_forecast_smoke[lags: [1, 3], trend: ct, seasonal: False, nexog: 2, periods: 11, missing: drop, pandas: False, hold_back12] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_parameterless_autoreg PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_predict_errors PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_spec_errors PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_ar_select_order_smoke PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAutoRegOLSConstant::test_params PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAutoRegOLSConstant::test_llf PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAutoRegOLSConstant::test_fpe PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAutoRegOLSConstant::test_pickle PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAutoRegOLSConstant::test_summary PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAutoRegOLSConstant::test_pvalues PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAutoRegOLSConstant::test_bse PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAutoRegOLSConstant::test_predict PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAutoRegOLSNoConstant::test_params PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAutoRegOLSNoConstant::test_llf PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAutoRegOLSNoConstant::test_fpe PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAutoRegOLSNoConstant::test_pickle PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAutoRegOLSNoConstant::test_summary PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAutoRegOLSNoConstant::test_pvalues PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAutoRegOLSNoConstant::test_bse PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::TestAutoRegOLSNoConstant::test_predict PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag0] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag1] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag2] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag3] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag4] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag5] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag6] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag7] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag8] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag9] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag10] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag11] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag12] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag13] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag14] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_info_criterion[lag15] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_named_series[True] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_named_series[False] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_series PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_ar_order_select PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_constant_column_trend PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_summary_corner[True] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_summary_corner[False] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_score PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_roots PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_equiv_dynamic PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_against_sarimax PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_predict_seasonal PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_predict_exog PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_predict_irregular_ar PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_forecast_start_end_equiv[True] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_forecast_start_end_equiv[False] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_start[21] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_start[25] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_deterministic PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_predict_forecast_equiv PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_forecast_period_index PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_plot_err PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_resids PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_predictions PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_dynamic_predictions_oos PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_invalid_dynamic PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_exog_prediction PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_old_names PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_diagnostic_summary_short PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_ar_model_predict PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_no_variables PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_removal PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_apply_exception PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-0-True-n] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-0-True-ct] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-0-False-n] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-0-False-ct] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-1-True-n] PASSED [ 94%] ../.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_ar.py::test_autoreg_append[True-1-True-ct] PASSED [ 94%] 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=============================== warnings summary =============================== base/tests/test_penalized.py: 2 warnings base/tests/test_shrink_pickle.py: 3 warnings discrete/tests/test_count_model.py: 2 warnings discrete/tests/test_discrete.py: 7 warnings tsa/statespace/tests/test_fixed_params.py: 1 warning tsa/statespace/tests/test_impulse_responses.py: 2 warnings tsa/statespace/tests/test_sarimax.py: 1 warning tsa/vector_ar/tests/test_svar.py: 101 warnings /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/model.py:607: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals warnings.warn("Maximum Likelihood optimization failed to " discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_fit_regularized discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_fit_regularized discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_fit_regularized discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_fit_regularized /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 1 out of 4 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers warnings.warn(message, ConvergenceWarning) discrete/tests/test_count_model.py: 8 warnings discrete/tests/test_discrete.py: 2 warnings discrete/tests/test_truncated_model.py: 1 warning /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/l1_solvers_common.py:144: ConvergenceWarning: Could not trim params automatically due to failed QC check. Trimming using trim_mode == 'size' will still work. warnings.warn(msg, ConvergenceWarning) discrete/tests/test_count_model.py::TestZeroInflatedModel_logit::test_fit_regularized discrete/tests/test_count_model.py::TestZeroInflatedModel_probit::test_fit_regularized discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_fit_regularized discrete/tests/test_count_model.py::TestZeroInflatedModelPandas::test_fit_regularized /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 2 out of 6 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers warnings.warn(message, ConvergenceWarning) discrete/tests/test_count_model.py::TestZeroInflatedModel_offset::test_fit_regularized /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 3 out of 4 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers warnings.warn(message, ConvergenceWarning) discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_fit_regularized /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 2 out of 5 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers warnings.warn(message, ConvergenceWarning) discrete/tests/test_count_model.py::TestZeroInflatedGeneralizedPoisson::test_fit_regularized /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 3 out of 7 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers warnings.warn(message, ConvergenceWarning) discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_null discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP_predict2::test_mean /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/model.py:595: HessianInversionWarning: Inverting hessian failed, no bse or cov_params available warnings.warn('Inverting hessian failed, no bse or cov_params ' discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_fit_regularized /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 1 out of 2 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers warnings.warn(message, ConvergenceWarning) discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_fit_regularized /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 1 out of 3 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers warnings.warn(message, ConvergenceWarning) discrete/tests/test_count_model.py::TestZeroInflatedNegativeBinomialP::test_fit_regularized /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 1 out of 5 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers warnings.warn(message, ConvergenceWarning) discrete/tests/test_discrete.py::TestPoissonL1Compatability::test_params discrete/tests/test_discrete.py::TestNegativeBinomialGeoL1Compatability::test_params discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_fit_regularized discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_fit_regularized discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_fit_regularized /usr/lib/python3/dist-packages/numpy/_core/fromnumeric.py:86: RuntimeWarning: overflow encountered in reduce return ufunc.reduce(obj, axis, dtype, out, **passkwargs) discrete/tests/test_discrete.py::test_perfect_prediction discrete/tests/test_discrete.py::test_perfect_prediction discrete/tests/test_discrete.py::test_perfect_prediction /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/discrete/discrete_model.py:227: PerfectSeparationWarning: Perfect separation or prediction detected, parameter may not be identified warnings.warn(msg, category=PerfectSeparationWarning) discrete/tests/test_discrete.py::test_negative_binomial_default_alpha_param /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/families/links.py:13: FutureWarning: The nbinom link alias is deprecated. Use NegativeBinomial instead. The nbinom link alias will be removed after the 0.15.0 release. warnings.warn( discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_fit_regularized /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 4 out of 10 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers warnings.warn(message, ConvergenceWarning) discrete/tests/test_discrete.py::TestGeneralizedPoisson_p1::test_fit_regularized /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 5 out of 11 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers warnings.warn(message, ConvergenceWarning) discrete/tests/test_predict.py::TestNegativeBinomialPPredict::test_influence discrete/tests/test_predict.py::TestNegativeBinomialPPredict::test_predict discrete/tests/test_predict.py::TestGeneralizedPoissonPredict::test_influence discrete/tests/test_truncated_model.py::TestHurdlePoissonR::test_predict /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/_prediction_inference.py:782: UserWarning: using default log-link in get_prediction warnings.warn("using default log-link in get_prediction") discrete/tests/test_predict.py::test_distr[case9] discrete/tests/test_predict.py::test_distr[case10] discrete/tests/test_predict.py::test_distr[case11] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/outliers_influence.py:545: RuntimeWarning: invalid value encountered in sqrt return sf / np.sqrt(hf) / np.sqrt(1 - self.hat_matrix_diag) discrete/tests/test_truncated_model.py::TestZeroTruncatedNBPModel::test_fit_regularized /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/base/l1_solvers_common.py:71: ConvergenceWarning: QC check did not pass for 2 out of 4 parameters Try increasing solver accuracy or number of iterations, decreasing alpha, or switch solvers warnings.warn(message, ConvergenceWarning) formula/tests/test_formula.py::TestFormulaPandas::test_summary formula/tests/test_formula.py::TestFormulaDict::test_summary regression/tests/test_regression.py::TestOLS::test_summary_slim /usr/lib/python3/dist-packages/scipy/stats/_axis_nan_policy.py:430: UserWarning: `kurtosistest` p-value may be inaccurate with fewer than 20 observations; only n=16 observations were given. return hypotest_fun_in(*args, **kwds) genmod/tests/test_gee.py::TestGEE::test_invalid_args[False-True] genmod/tests/test_gee.py::TestGEE::test_invalid_args[True-True] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/generalized_linear_model.py:314: RuntimeWarning: divide by zero encountered in log exposure = np.log(exposure) graphics/tests/test_functional.py: 320 warnings /usr/lib/python3.13/multiprocessing/popen_fork.py:67: DeprecationWarning: This process (pid=23003) is multi-threaded, use of fork() may lead to deadlocks in the child. self.pid = os.fork() nonparametric/tests/test_kernel_density.py::TestKDEMultivariateConditional::test_unordered_CV_LS /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/kernel_density.py:679: RuntimeWarning: invalid value encountered in scalar divide CV += (G / m_x ** 2) - 2 * (f_X_Y / m_x) nonparametric/tests/test_kernel_regression.py::TestKernelReg::test_continuousdata_lc_cvls /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/kernel_regression.py:251: RuntimeWarning: invalid value encountered in divide B_x = (G_numer * d_fx - G_denom * d_mx) / (G_denom**2) nonparametric/tests/test_lowess.py::TestLowess::test_duplicate_xs /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/nonparametric/smoothers_lowess.py:226: RuntimeWarning: invalid value encountered in divide res, _ = _lowess(y, x, x, np.ones_like(x), regression/tests/test_dimred.py::test_covreduce /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/regression/dimred.py:694: ConvergenceWarning: CovReduce optimization did not converge, |g|=1.287955 warnings.warn(msg, ConvergenceWarning) robust/tests/test_scale.py::TestHuberAxes::test_axis1 /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/robust/scale.py:292: RuntimeWarning: divide by zero encountered in divide subset = np.less_equal(np.abs((a - mu) / scale), self.c) sandbox/tests/test_gam.py::TestGAMGaussianLogLink::test_predict /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/sandbox/gam.py:327: IterationLimitWarning: Maximum iteration reached. warnings.warn(iteration_limit_doc, IterationLimitWarning) sandbox/tests/test_gam.py::TestGAMNegativeBinomial::test_predict /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/families/family.py:1367: ValueWarning: Negative binomial dispersion parameter alpha not set. Using default value alpha=1.0. warnings.warn("Negative binomial dispersion parameter alpha not " stats/tests/test_corrpsd.py::TestCovPSD::test_cov_nearest stats/tests/test_corrpsd.py::TestCorrPSD1::test_nearest stats/tests/test_corrpsd.py::test_corrpsd_threshold[0] stats/tests/test_corrpsd.py::test_corrpsd_threshold[1e-15] stats/tests/test_corrpsd.py::test_corrpsd_threshold[1e-10] stats/tests/test_corrpsd.py::test_corrpsd_threshold[1e-06] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/correlation_tools.py:89: IterationLimitWarning: Maximum iteration reached. warnings.warn(iteration_limit_doc, IterationLimitWarning) stats/tests/test_descriptivestats.py::test_description_basic stats/tests/test_descriptivestats.py::test_empty_columns stats/tests/test_descriptivestats.py::test_empty_columns /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/descriptivestats.py:406: SmallSampleWarning: One or more sample arguments is too small; all returned values will be NaN. See documentation for sample size requirements. mode_res = stats.mode(ser_no_missing, **kwargs) stats/tests/test_power.py::test_power_solver_warn /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/power.py:132: RuntimeWarning: invalid value encountered in sqrt pow_ = stats.norm.sf(crit - d*np.sqrt(nobs)/sigma) stats/tests/test_tost.py::test_tost_asym /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/stats/weightstats.py:1479: RuntimeWarning: invalid value encountered in log low = transform(low) tsa/base/tests/test_tsa_indexes.py::test_instantiation_valid tsa/base/tests/test_tsa_indexes.py::test_instantiation_valid tsa/base/tests/test_tsa_indexes.py::test_instantiation_valid tsa/base/tests/test_tsa_indexes.py::test_instantiation_valid /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/base/tsa_model.py:559: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format. _index = to_datetime(index) tsa/holtwinters/tests/test_holtwinters.py::TestHoltWinters::test_holt_damp_r tsa/holtwinters/tests/test_holtwinters.py::test_no_params_to_optimize /usr/lib/python3/dist-packages/pandas/util/_decorators.py:213: EstimationWarning: Model has no free parameters to estimate. Set optimized=False to suppress this warning return func(*args, **kwargs) tsa/holtwinters/tests/test_holtwinters.py::test_alternative_minimizers[TNC] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/holtwinters/model.py:903: ConvergenceWarning: Optimization failed to converge. Check mle_retvals. warnings.warn( tsa/holtwinters/tests/test_holtwinters.py::test_alternative_minimizers[trust-constr] /usr/lib/python3/dist-packages/scipy/optimize/_differentiable_functions.py:317: UserWarning: delta_grad == 0.0. Check if the approximated function is linear. If the function is linear better results can be obtained by defining the Hessian as zero instead of using quasi-Newton approximations. self.H.update(self.x - self.x_prev, self.g - self.g_prev) tsa/holtwinters/tests/test_holtwinters.py::test_forecast_index_types[irregular] tsa/holtwinters/tests/test_holtwinters.py::test_invalid_index /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/base/tsa_model.py:837: FutureWarning: No supported index is available. In the next version, calling this method in a model without a supported index will result in an exception. return get_prediction_index( tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py::test_em_nonstationary tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py::test_em_nonstationary /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/genmod/generalized_linear_model.py:898: RuntimeWarning: divide by zero encountered in scalar divide return np.sum(resid / self.family.variance(mu)) / self.df_resid tsa/statespace/tests/test_dynamic_factor_mq_monte_carlo.py::test_em_nonstationary /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/dynamic_factor_mq.py:2695: UserWarning: EM reached maximum number of iterations (2), without achieving convergence: llf=-23.123, convergence criterion=1.8362 (while specified tolerance was 1e-06) warn(f'EM reached maximum number of iterations ({maxiter}),' tsa/statespace/tests/test_mlemodel.py::test_integer_params /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/kalman_filter.py:1762: RuntimeWarning: invalid value encountered in scalar divide self.scale = np.sum(scale_obs[d:]) / nobs_k_endog tsa/statespace/tests/test_sarimax.py::test_plot_too_few_obs /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/mlemodel.py:1235: RuntimeWarning: invalid value encountered in divide np.inner(score_obs, score_obs) / tsa/statespace/tests/test_sarimax.py::test_plot_too_few_obs /usr/lib/python3/dist-packages/numpy/_core/fromnumeric.py:4268: RuntimeWarning: Degrees of freedom <= 0 for slice return _methods._var(a, axis=axis, dtype=dtype, out=out, ddof=ddof, tsa/statespace/tests/test_sarimax.py::test_plot_too_few_obs /usr/lib/python3/dist-packages/numpy/_core/_methods.py:181: RuntimeWarning: invalid value encountered in divide arrmean = um.true_divide(arrmean, div, out=arrmean, tsa/statespace/tests/test_sarimax.py::test_plot_too_few_obs /usr/lib/python3/dist-packages/numpy/_core/_methods.py:215: RuntimeWarning: invalid value encountered in scalar divide ret = ret.dtype.type(ret / rcount) tsa/statespace/tests/test_sarimax.py::test_sarimax_starting_values_few_obsevations_long_ma tsa/tests/test_stattools.py::test_arma_order_select_ic /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/statespace/sarimax.py:978: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters. warn('Non-invertible starting MA parameters found.' tsa/stl/tests/test_mstl.py::test_number_of_seasonal_components[data-periods2-None-2] tsa/stl/tests/test_mstl.py::test_output_invariant_to_period_order[data-periods_ordered1-windows_ordered1-periods_not_ordered1-windows_not_ordered1] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/stl/mstl.py:218: UserWarning: A period(s) is larger than half the length of time series. Removing these period(s). warnings.warn( tsa/tests/test_exponential_smoothing.py::test_hessian /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_exponential_smoothing.py:669: PrecisionWarning: Calculation of the Hessian using finite differences is usually subject to substantial approximation errors. austourists_model_fit.model.hessian( tsa/tests/test_exponential_smoothing.py::test_seasonal_order[heuristic] /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/exponential_smoothing/ets.py:1448: RuntimeWarning: invalid value encountered in divide self.standardized_forecasts_error = ( tsa/tests/test_stattools.py::TestBreakvarHeteroskedasticityTest::test_2d_input_with_missing_values /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_stattools.py:461: UserWarning: Later subset of data for variable 2 has too few non-missing observations to calculate test statistic. actual_statistic, actual_pvalue = breakvar_heteroskedasticity_test( tsa/tests/test_stattools.py::TestKPSS::test_none /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/tests/test_stattools.py:890: InterpolationWarning: The test statistic is outside of the range of p-values available in the look-up table. The actual p-value is smaller than the p-value returned. kpss(self.x, nlags=None) tsa/tests/test_stattools.py::test_pacf_1_obs /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/regression/linear_model.py:1483: RuntimeWarning: invalid value encountered in scalar divide r[k] = (x[0:-k] * x[k:]).sum() / (n - k * adj_needed) tsa/tests/test_stattools.py::test_pacf_1_obs /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/regression/linear_model.py:1490: ValueWarning: Matrix is singular. Using pinv. warnings.warn("Matrix is singular. Using pinv.", ValueWarning) tsa/vector_ar/tests/test_var.py::test_irf_err_bands tsa/vector_ar/tests/test_var.py::test_irf_err_bands /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/irf.py:528: ComplexWarning: Casting complex values to real discards the imaginary part W[i,j,:,:], eigva[i,j,:,0], k[i,j] = util.eigval_decomp(cov_hold[i,j,:,:]) tsa/vector_ar/tests/test_var.py::test_irf_err_bands /build/reproducible-path/statsmodels-0.14.5+dfsg/.pybuild/cpython3_3.13_statsmodels/build/statsmodels/tsa/vector_ar/irf.py:483: ComplexWarning: Casting complex values to real discards the imaginary part W[i], eigva[i], k[i] = util.eigval_decomp(stack_cov[i]) -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html = 17541 passed, 305 skipped, 140 xfailed, 2 xpassed, 539 warnings in 1195.57s (0:19:55) = make[1]: Leaving directory '/build/reproducible-path/statsmodels-0.14.5+dfsg' create-stamp debian/debhelper-build-stamp dh_testroot -i -O--buildsystem=pybuild dh_prep -i -O--buildsystem=pybuild dh_auto_install -i -O--buildsystem=pybuild I: pybuild plugin_pyproject:178: Copying package built for python3.13 to destdir debian/rules execute_after_dh_auto_install make[1]: Entering directory '/build/reproducible-path/statsmodels-0.14.5+dfsg' : # Remove compiled due to testing files find debian -name *.pyc -delete rm -f debian/*/usr/lib/*/dist-packages/enet_poisson.csv debian/*/usr/lib/*/dist-packages/enet_binomial.csv : # strip docs/ since they aren't really a Python module, there is -doc for it : # TODO find debian -wholename \*scikits/statsmodels/docs | xargs rm -rf : # remove other unnecessary files rm -fv debian/*/usr/setup.cfg find debian -iname COPYING -o -iname LICENSE* | xargs -r rm -fv removed 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels-0.14.5+dfsg.dist-info/licenses/LICENSE.txt' removed 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/stats/libqsturng/LICENSE.txt' removed 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/LICENSE.txt' : # move binary libraries into -lib for PACKAGE_NAME in python3-statsmodels; do \ for lib in $(find debian/${PACKAGE_NAME}/usr -name '*.so'); do \ sdir=$(dirname $lib) ; \ tdir=debian/${PACKAGE_NAME}-lib/${sdir#*${PACKAGE_NAME}/} ; \ mkdir -p $tdir ; \ echo "I: Moving '$lib' into '$tdir'." ; \ mv $lib $tdir ; \ done ; \ done I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/_innovations.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_simulation_smoother.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_tools.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_cfa_simulation_smoother.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_filters/_univariate_diffuse.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_filters'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_filters/_inversions.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_filters'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_filters/_conventional.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_filters'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_filters/_univariate.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_filters'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_kalman_smoother.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_representation.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_kalman_filter.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_smoothers/_univariate_diffuse.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_smoothers'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_smoothers/_classical.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_smoothers'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_smoothers/_alternative.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_smoothers'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_smoothers/_conventional.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_smoothers'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_smoothers/_univariate.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_smoothers'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace/_initialization.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/statespace'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/holtwinters/_exponential_smoothers.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/holtwinters'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/innovations/_arma_innovations.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/innovations'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/stl/_stl.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/stl'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/regime_switching/_kim_smoother.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/regime_switching'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/regime_switching/_hamilton_filter.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/regime_switching'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/tsa/exponential_smoothing/_ets_smooth.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/tsa/exponential_smoothing'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/nonparametric/_smoothers_lowess.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/nonparametric'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/nonparametric/linbin.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/nonparametric'. I: Moving 'debian/python3-statsmodels/usr/lib/python3.13/dist-packages/statsmodels/robust/_qn.cpython-313-x86_64-linux-gnu.so' into 'debian/python3-statsmodels-lib/usr/lib/python3.13/dist-packages/statsmodels/robust'. make[1]: Leaving directory '/build/reproducible-path/statsmodels-0.14.5+dfsg' dh_installdocs -i -O--buildsystem=pybuild dh_installdocs: warning: Cannot auto-detect main package for python-statsmodels-doc. If the default is wrong, please use --doc-main-package dh_sphinxdoc -i -O--buildsystem=pybuild dh_sphinxdoc: warning: ignoring unknown JavaScript code: debian/python-statsmodels-doc/usr/share/doc/python-statsmodels-doc/html/_static/facebox.js dh_sphinxdoc: warning: ignoring unknown JavaScript code: debian/python-statsmodels-doc/usr/share/doc/python-statsmodels-doc/html/_static/mktree.js dh_sphinxdoc: warning: ignoring unknown JavaScript code: debian/python-statsmodels-doc/usr/share/doc/python-statsmodels-doc/html/_static/scripts.js dh_installchangelogs -i -O--buildsystem=pybuild dh_installexamples -i -O--buildsystem=pybuild dh_installexamples: warning: Cannot auto-detect main package for python-statsmodels-doc. If the default is wrong, please use --doc-main-package dh_python3 -i -O--buildsystem=pybuild I: dh_python3 pydist:339: Ignoring complex environment marker: pywinpty; os_name == "nt" and extra == "develop" dh_installsystemduser -i -O--buildsystem=pybuild dh_lintian -i -O--buildsystem=pybuild dh_perl -i -O--buildsystem=pybuild debian/rules execute_before_dh_link make[1]: Entering directory '/build/reproducible-path/statsmodels-0.14.5+dfsg' : # deduplicate images - the ||true is because we only build-depend on jdupes if we're building documentation jdupes -r -l debian/python-statsmodels-doc/usr/share/doc || true make[1]: Leaving directory '/build/reproducible-path/statsmodels-0.14.5+dfsg' dh_link -i -O--buildsystem=pybuild dh_strip_nondeterminism -i -O--buildsystem=pybuild debian/rules override_dh_compress make[1]: Entering directory '/build/reproducible-path/statsmodels-0.14.5+dfsg' dh_compress -X.py -X.html -X.pdf -X.css -X.jpg -X.txt -X.js -X.json -X.rtc -X.inv -Xobjects.inv make[1]: Leaving directory '/build/reproducible-path/statsmodels-0.14.5+dfsg' dh_fixperms -i -O--buildsystem=pybuild debian/rules execute_after_dh_fixperms make[1]: Entering directory '/build/reproducible-path/statsmodels-0.14.5+dfsg' find debian -name "*.txt" -exec chmod -x \{\} \; make[1]: Leaving directory '/build/reproducible-path/statsmodels-0.14.5+dfsg' dh_missing -i -O--buildsystem=pybuild dh_installdeb -i -O--buildsystem=pybuild dh_numpy3 -i -O--buildsystem=pybuild Possible precedence issue with control flow operator (return) at /usr/bin/dh_numpy3 line 57. dh_gencontrol -i -O--buildsystem=pybuild dpkg-gencontrol: warning: Provides field of package python3-statsmodels: substitution variable ${python3:Provides} used, but is not defined dpkg-gencontrol: warning: package python-statsmodels-doc: substitution variable ${sphinxdoc:Built-Using} unused, but is defined dh_md5sums -i -O--buildsystem=pybuild dh_builddeb -i -O--buildsystem=pybuild dpkg-deb: building package 'python-statsmodels-doc' in '../python-statsmodels-doc_0.14.5+dfsg-1_all.deb'. dpkg-deb: building package 'python3-statsmodels' in '../python3-statsmodels_0.14.5+dfsg-1_all.deb'. dpkg-genbuildinfo --build=all -O../statsmodels_0.14.5+dfsg-1_all.buildinfo dpkg-genchanges --build=all -O../statsmodels_0.14.5+dfsg-1_all.changes dpkg-genchanges: info: binary-only arch-indep upload (source code and arch-specific packages not included) dpkg-source --after-build . dpkg-buildpackage: info: binary-only upload (no source included) -------------------------------------------------------------------------------- Build finished at 2025-10-02T09:25:51Z Finished -------- I: Built successfully +------------------------------------------------------------------------------+ | Changes Thu, 02 Oct 2025 09:25:52 +0000 | +------------------------------------------------------------------------------+ statsmodels_0.14.5+dfsg-1_all.changes: -------------------------------------- Format: 1.8 Date: Sun, 10 Aug 2025 14:13:47 +0100 Source: statsmodels Binary: python-statsmodels-doc python3-statsmodels Architecture: all Version: 0.14.5+dfsg-1 Distribution: unstable Urgency: medium Maintainer: Debian Science Maintainers Changed-By: Rebecca N. Palmer Description: python-statsmodels-doc - documentation and examples for statsmodels python3-statsmodels - Python3 module for the estimation of statistical models Closes: 1109960 Changes: statsmodels (0.14.5+dfsg-1) unstable; urgency=medium . * New upstream release. (Closes: #1109960) Refresh patches. * Update d/copyright. * Remove obsolete README.source. * Tighten (Build-)Depends versions. * Re-add intersphinx Build-Depends. * Bump Standards-Version to 4.7.2 (no changes needed). * Use pybuild-plugin-pyproject. * Simplify d/rules, list deleted files, use more modern dh style (dh-sequence*, execute_before/after*). * Docs: build-depend on pickleshare for bookmarks, build .py examples from .ipynb with python3 shebang. * Docs reproducibility: strip ipykernel IDs and more times, strip before indexing, fix another random seed. 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+------------------------------------------------------------------------------+ | Buildinfo Thu, 02 Oct 2025 09:25:52 +0000 | +------------------------------------------------------------------------------+ Format: 1.0 Source: statsmodels Binary: python-statsmodels-doc python3-statsmodels Architecture: all Version: 0.14.5+dfsg-1 Checksums-Md5: 5316cb9610549e4e885155f96f2d2231 51933768 python-statsmodels-doc_0.14.5+dfsg-1_all.deb 32e6fd7950e5ab3ad89791f2bb7cdf3d 4826544 python3-statsmodels_0.14.5+dfsg-1_all.deb Checksums-Sha1: 8e4c5283ee307a174bf928904f2bef0057efd731 51933768 python-statsmodels-doc_0.14.5+dfsg-1_all.deb 30e2f00918df99a2b4fd41ee08d6257359348ca8 4826544 python3-statsmodels_0.14.5+dfsg-1_all.deb Checksums-Sha256: 26f9df144f55d079b0acc4b5a106769e670edca14b601f647fedc078e70d5761 51933768 python-statsmodels-doc_0.14.5+dfsg-1_all.deb 7d0a72351b480ec18eac836c6ab7a1e3a2591b7f07eb5977116694ccf51a27dc 4826544 python3-statsmodels_0.14.5+dfsg-1_all.deb Build-Origin: Debian Build-Architecture: amd64 Build-Date: Thu, 02 Oct 2025 09:25:50 +0000 Build-Path: /build/reproducible-path/statsmodels-0.14.5+dfsg Installed-Build-Depends: autoconf (= 2.72-3.1), automake (= 1:1.17-4), autopoint (= 0.23.1-2), autotools-dev (= 20240727.1), base-files (= 14), base-passwd (= 3.6.7), bash (= 5.2.37-2+b5), binutils (= 2.45-4), binutils-common (= 2.45-4), binutils-x86-64-linux-gnu (= 2.45-4), blt (= 2.5.3+dfsg-8), bsdextrautils (= 2.41.1-1), bsdutils (= 1:2.41.1-1), build-essential (= 12.12), bzip2 (= 1.0.8-6), ca-certificates (= 20250419), coreutils (= 9.7-3), cpp (= 4:14.2.0-1), cpp-14 (= 14.3.0-5), cpp-14-x86-64-linux-gnu (= 14.3.0-5), cpp-x86-64-linux-gnu (= 4:14.2.0-1), cython3 (= 3.0.11+dfsg-2+b1), dash (= 0.5.12-12), debconf (= 1.5.91), debhelper (= 13.26), debianutils (= 5.23.2), dh-autoreconf (= 20), dh-python (= 6.20250414), dh-strip-nondeterminism (= 1.14.2-1), diffutils (= 1:3.10-4), docutils-common (= 0.21.2+dfsg-2), dpkg (= 1.22.21), dpkg-dev (= 1.22.21), dwz (= 0.15-1+b1), file (= 1:5.46-5), findutils (= 4.10.0-3), fontconfig (= 2.15.0-2.3), fontconfig-config (= 2.15.0-2.3), fonts-dejavu-core (= 2.37-8), fonts-dejavu-mono (= 2.37-8), fonts-font-awesome (= 5.0.10+really4.7.0~dfsg-4.1), fonts-glyphicons-halflings (= 1.009~3.4.1+dfsg-6), fonts-lyx (= 2.4.3-1), fonts-mathjax (= 2.7.9+dfsg-1), fonts-open-sans (= 1.11-2), g++ (= 4:14.2.0-1), g++-14 (= 14.3.0-5), g++-14-x86-64-linux-gnu (= 14.3.0-5), g++-x86-64-linux-gnu (= 4:14.2.0-1), gcc (= 4:14.2.0-1), gcc-14 (= 14.3.0-5), gcc-14-base (= 14.3.0-5), gcc-14-x86-64-linux-gnu (= 14.3.0-5), gcc-15-base (= 15.2.0-2), gcc-x86-64-linux-gnu (= 4:14.2.0-1), gdb (= 16.3-4), gettext (= 0.23.1-2+b1), gettext-base (= 0.23.1-2+b1), grep (= 3.11-4), groff-base (= 1.23.0-9), gzip (= 1.13-1), hostname (= 3.25), init-system-helpers (= 1.69), intltool-debian (= 0.35.0+20060710.6), jdupes (= 1.28.0-1), libabsl20240722 (= 20240722.0-4), libacl1 (= 2.3.2-2+b1), libamd3 (= 1:7.11.0+dfsg-1), libaom3 (= 3.12.1-1), libarchive-zip-perl (= 1.68-1), libargon2-1 (= 0~20190702+dfsg-5), libasan8 (= 15.2.0-2), libatomic1 (= 15.2.0-2), libattr1 (= 1:2.5.2-3), libaudit-common (= 1:4.0.5-1), libaudit1 (= 1:4.0.5-1), libavif16 (= 1.3.0-1), libbabeltrace1 (= 1.5.11-4+b2), libbinutils (= 2.45-4), libblas3 (= 3.12.1-6), libblkid1 (= 2.41.1-1), libbrotli1 (= 1.1.0-2+b7), libbsd0 (= 0.12.2-2), libbz2-1.0 (= 1.0.8-6), libc-bin (= 2.41-12), libc-dev-bin (= 2.41-12), libc6 (= 2.41-12), libc6-dev (= 2.41-12), libcairo2 (= 1.18.4-1+b1), libcamd3 (= 1:7.11.0+dfsg-1), libcap-ng0 (= 0.8.5-4+b1), libcap2 (= 1:2.75-10+b1), libcc1-0 (= 15.2.0-2), libccolamd3 (= 1:7.11.0+dfsg-1), libcholmod5 (= 1:7.11.0+dfsg-1), libcolamd3 (= 1:7.11.0+dfsg-1), libcom-err2 (= 1.47.2-3+b3), libcrypt-dev (= 1:4.4.38-1), libcrypt1 (= 1:4.4.38-1), libctf-nobfd0 (= 2.45-4), libctf0 (= 2.45-4), libcurl3t64-gnutls (= 8.16.0~rc2-1), libcurl4t64 (= 8.16.0~rc2-1), libdatrie1 (= 0.2.13-4), libdav1d7 (= 1.5.1-1), libdb5.3t64 (= 5.3.28+dfsg2-9), libdebconfclient0 (= 0.280), libdebhelper-perl (= 13.26), libdebuginfod-common (= 0.192-4), libdebuginfod1t64 (= 0.192-4), libdeflate0 (= 1.23-2), libdpkg-perl (= 1.22.21), libdsdp-5.8t64 (= 5.8-10.1), libdw1t64 (= 0.192-4), libelf1t64 (= 0.192-4), libexpat1 (= 2.7.1-2), libexpat1-dev (= 2.7.1-2), libffi8 (= 3.4.8-2), libfftw3-double3 (= 3.3.10-2+b1), libfile-stripnondeterminism-perl (= 1.14.2-1), libfontconfig1 (= 2.15.0-2.3), libfreetype6 (= 2.13.3+dfsg-1), libfribidi0 (= 1.0.16-1), libgav1-1 (= 0.19.0-3+b1), libgcc-14-dev (= 14.3.0-5), libgcc-s1 (= 15.2.0-2), libgcrypt20 (= 1.11.2-2), libgdbm-compat4t64 (= 1.26-1), libgdbm6t64 (= 1.26-1), libgfortran5 (= 15.2.0-2), libglib2.0-0t64 (= 2.84.4-3), libglpk40 (= 5.0-2), libgmp10 (= 2:6.3.0+dfsg-4), libgnutls30t64 (= 3.8.10-2), libgomp1 (= 15.2.0-2), libgpg-error0 (= 1.55-2), libgprofng0 (= 2.45-4), libgraphite2-3 (= 1.3.14-3), libgsl28 (= 2.8+dfsg-5), libgslcblas0 (= 2.8+dfsg-5), libgssapi-krb5-2 (= 1.21.3-5), libharfbuzz0b (= 10.2.0-1+b1), libhogweed6t64 (= 3.10.1-1), libhwasan0 (= 15.2.0-2), libice6 (= 2:1.1.1-1), libicu76 (= 76.1-4), libidn2-0 (= 2.3.8-4), libimagequant0 (= 4.4.0-3), libipt2 (= 2.1.2-1), libisl23 (= 0.27-1), libitm1 (= 15.2.0-2), libjansson4 (= 2.14-2+b3), libjbig0 (= 2.1-6.1+b2), libjodycode3t64 (= 3.1.2-1), libjpeg62-turbo (= 1:2.1.5-4), libjs-backbone (= 1.4.1~dfsg+~1.4.15-3), libjs-bootstrap (= 3.4.1+dfsg-6), libjs-bootstrap-tour (= 0.12.0+dfsg-5), libjs-codemirror (= 5.65.20+~cs5.83.25-1), libjs-es6-promise (= 4.2.8-12), libjs-jed (= 1.1.1-4), libjs-jquery (= 3.7.1+dfsg+~3.5.33-1), libjs-jquery-typeahead (= 2.11.0+dfsg1-3), libjs-jquery-ui (= 1.13.2+dfsg-1), libjs-marked (= 4.2.3+ds+~4.0.7-4), libjs-mathjax (= 2.7.9+dfsg-1), libjs-moment (= 2.29.4+ds-1), libjs-requirejs (= 2.3.7+ds+~2.1.37-1), libjs-requirejs-text (= 2.0.12-1.1), libjs-sphinxdoc (= 8.2.3-2), libjs-text-encoding (= 0.7.0-5), libjs-underscore (= 1.13.4~dfsg+~1.11.4-3), libjs-xterm (= 5.3.0-4), libjson-c5 (= 0.18+ds-1), libjson-perl (= 4.10000-1), libk5crypto3 (= 1.21.3-5), libkeyutils1 (= 1.6.3-6), libkrb5-3 (= 1.21.3-5), libkrb5support0 (= 1.21.3-5), liblapack3 (= 3.12.1-6), liblastlog2-2 (= 2.41.1-1), liblcms2-2 (= 2.16-2), libldap2 (= 2.6.10+dfsg-1), liblerc4 (= 4.0.0+ds-5), liblsan0 (= 15.2.0-2), libltdl7 (= 2.5.4-4), liblua5.4-0 (= 5.4.8-1), liblz4-1 (= 1.10.0-4), liblzma5 (= 5.8.1-1), libmagic-mgc (= 1:5.46-5), libmagic1t64 (= 1:5.46-5), libmd0 (= 1.1.0-2+b1), libmount1 (= 2.41.1-1), libmpc3 (= 1.3.1-1+b3), libmpfr6 (= 4.2.2-1), libncursesw6 (= 6.5+20250216-2), libnettle8t64 (= 3.10.1-1), libnghttp2-14 (= 1.64.0-1.1+b1), libnghttp3-9 (= 1.8.0-1), libngtcp2-16 (= 1.11.0-1), libngtcp2-crypto-gnutls8 (= 1.11.0-1), libnlopt0 (= 2.7.1-6+b4), libnorm1t64 (= 1.5.9+dfsg-3.1+b2), libnuma1 (= 2.0.19-1), libopenjp2-7 (= 2.5.3-2.1), libp11-kit0 (= 0.25.5-3), libpam-modules (= 1.7.0-5), libpam-modules-bin (= 1.7.0-5), libpam-runtime (= 1.7.0-5), libpam0g (= 1.7.0-5), libpango-1.0-0 (= 1.56.3-1), libpangocairo-1.0-0 (= 1.56.3-1), libpangoft2-1.0-0 (= 1.56.3-1), libpaper-utils (= 2.2.5-0.3+b2), libpaper2 (= 2.2.5-0.3+b2), libpcre2-8-0 (= 10.45-1), libperl5.40 (= 5.40.1-6), libpgm-5.3-0t64 (= 5.3.128~dfsg-2.1+b1), libpipeline1 (= 1.5.8-1), libpixman-1-0 (= 0.44.0-3), libpng16-16t64 (= 1.6.50-1), libproc2-0 (= 2:4.0.4-9), libpsl5t64 (= 0.21.2-1.1+b1), libpython3-all-dev (= 3.13.7-1), libpython3-dev (= 3.13.7-1), libpython3-stdlib (= 3.13.7-1), libpython3.13 (= 3.13.7-1), libpython3.13-dev (= 3.13.7-1), libpython3.13-minimal (= 3.13.7-1), libpython3.13-stdlib (= 3.13.7-1), libqhull-r8.0 (= 2020.2-6+b2), libquadmath0 (= 15.2.0-2), libraqm0 (= 0.10.3-1), librav1e0.7 (= 0.7.1-9+b2), libreadline8t64 (= 8.3-2), librtmp1 (= 2.4+20151223.gitfa8646d.1-3), libsasl2-2 (= 2.1.28+dfsg1-9), libsasl2-modules-db (= 2.1.28+dfsg1-9), libseccomp2 (= 2.6.0-2), libselinux1 (= 3.8.1-1), libsframe2 (= 2.45-4), libsharpyuv0 (= 1.5.0-0.1), libsm6 (= 2:1.2.6-1), libsmartcols1 (= 2.41.1-1), libsodium23 (= 1.0.18-1+b2), libsource-highlight-common (= 3.1.9-4.3), libsource-highlight4t64 (= 3.1.9-4.3+b1), libsqlite3-0 (= 3.46.1-7), libssh2-1t64 (= 1.11.1-1), libssl3t64 (= 3.5.2-1), libstdc++-14-dev (= 14.3.0-5), libstdc++6 (= 15.2.0-2), libsuitesparseconfig7 (= 1:7.11.0+dfsg-1), libsvtav1enc2 (= 2.3.0+dfsg-1), libsystemd0 (= 258~rc3-1), libtasn1-6 (= 4.20.0-2), libtcl8.6 (= 8.6.17+dfsg-1), libtext-charwidth-perl (= 0.04-11+b4), libtext-wrapi18n-perl (= 0.06-10), libthai-data (= 0.1.29-2), libthai0 (= 0.1.29-2+b1), libtiff6 (= 4.7.0-4), libtinfo6 (= 6.5+20250216-2), libtirpc-common (= 1.3.6+ds-1), libtirpc3t64 (= 1.3.6+ds-1), libtk8.6 (= 8.6.17-1), libtool (= 2.5.4-4), libtsan2 (= 15.2.0-2), libubsan1 (= 15.2.0-2), libuchardet0 (= 0.0.8-1+b2), libudev1 (= 258~rc3-1), libumfpack6 (= 1:7.11.0+dfsg-1), libunistring5 (= 1.3-2), libuuid1 (= 2.41.1-1), libwebp7 (= 1.5.0-0.1), libwebpdemux2 (= 1.5.0-0.1), libwebpmux3 (= 1.5.0-0.1), libx11-6 (= 2:1.8.12-1), libx11-data (= 2:1.8.12-1), libxau6 (= 1:1.0.11-1), libxcb-render0 (= 1.17.0-2+b1), libxcb-shm0 (= 1.17.0-2+b1), libxcb1 (= 1.17.0-2+b1), libxdmcp6 (= 1:1.1.5-1), libxext6 (= 2:1.3.4-1+b3), libxft2 (= 2.3.6-1+b4), libxml2-16 (= 2.14.5+dfsg-0.2), libxrender1 (= 1:0.9.12-1), libxslt1.1 (= 1.1.43-0.2), libxss1 (= 1:1.2.3-1+b3), libxt6t64 (= 1:1.2.1-1.2+b2), libxxhash0 (= 0.8.3-2), libyaml-0-2 (= 0.2.5-2), libyuv0 (= 0.0.1916.20250814-1), libzmq5 (= 4.3.5-1+b3), libzopfli1 (= 1.0.3-3), libzstd1 (= 1.5.7+dfsg-1), linux-libc-dev (= 6.16.3-1), littler (= 0.3.21-1), m4 (= 1.4.19-8), make (= 4.4.1-2), man-db (= 2.13.1-1), mawk (= 1.3.4.20250131-1), media-types (= 13.0.0), ncurses-base (= 6.5+20250216-2), ncurses-bin (= 6.5+20250216-2), netbase (= 6.5), node-jed (= 1.1.1-4), openssl (= 3.5.2-1), openssl-provider-legacy (= 3.5.2-1), pandoc (= 3.1.11.1+ds-3), pandoc-data (= 3.1.11.1-3), patch (= 2.8-2), perl (= 5.40.1-6), perl-base (= 5.40.1-6), perl-modules-5.40 (= 5.40.1-6), po-debconf (= 1.0.21+nmu1), procps (= 2:4.0.4-9), pybuild-plugin-pyproject (= 6.20250414), python-babel-localedata (= 2.17.0-1), python-matplotlib-data (= 3.10.1+dfsg1-4), python-matplotlib-doc (= 3.10.1+dfsg1-4), python-numpy-doc (= 1:2.2.4+ds-1), python-pandas-doc (= 2.2.3+dfsg-9), python-scipy-doc (= 1.15.3-1), python-tinycss2-common (= 1.4.0-2), python3 (= 3.13.7-1), python3-alabaster (= 0.7.16-0.1), python3-all (= 3.13.7-1), python3-all-dev (= 3.13.7-1), python3-argon2 (= 25.1.0-2), python3-argon2-cffi-bindings (= 25.1.0-2), python3-asttokens (= 3.0.0-2), python3-attr (= 25.3.0-1), python3-autocommand (= 2.2.2-3), python3-babel (= 2.17.0-1), python3-bleach (= 6.2.0-1), python3-brotli (= 1.1.0-2+b7), python3-bs4 (= 4.13.4-4), python3-build (= 1.2.2-4), python3-certifi (= 2025.1.31+ds-1), python3-cffi (= 2.0.0~b1-1), python3-cffi-backend (= 2.0.0~b1-1), python3-chardet (= 5.2.0+dfsg-2), python3-charset-normalizer (= 3.4.3-1), python3-colorama (= 0.4.6-4), python3-comm (= 0.2.1-1), python3-contourpy (= 1.3.1-2), python3-coverage (= 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11.3.0-1), python3-pil.imagetk (= 11.3.0-1), python3-pkg-resources (= 78.1.1-0.1), python3-platformdirs (= 4.3.7-1), python3-pluggy (= 1.6.0-1), python3-ply (= 3.11-9), python3-prometheus-client (= 0.21.1+ds1-1), python3-prompt-toolkit (= 3.0.52-1), python3-psutil (= 7.0.0-2), python3-ptyprocess (= 0.7.0-6), python3-pure-eval (= 0.2.3-1), python3-py (= 1.11.0-5), python3-pycparser (= 2.22-2), python3-pygments (= 2.18.0+dfsg-2), python3-pyparsing (= 3.1.2-1), python3-pyproject-hooks (= 1.2.0-1), python3-pytest (= 8.4.1-1), python3-pytest-forked (= 1.6.0-3), python3-pytz (= 2025.2-3), python3-referencing (= 0.36.2-1), python3-requests (= 2.32.5+dfsg-1), python3-roman (= 5.1-1), python3-roman-numerals (= 3.1.0-2), python3-rpds-py (= 0.21.0-2+b1), python3-rpy2 (= 3.5.17-2), python3-scipy (= 1.15.3-1), python3-seaborn (= 0.13.2-5), python3-send2trash (= 1.8.3-1), python3-setuptools (= 78.1.1-0.1), python3-setuptools-scm (= 8.2.1-2), python3-simplegeneric (= 0.8.1-5), python3-snowballstemmer (= 3.0.1-1), python3-soupsieve (= 2.7-2), python3-sphinx (= 8.2.3-2), python3-stack-data (= 0.6.3-1), python3-sympy (= 1.14.0-2), python3-terminado (= 0.18.1-1), python3-tinycss2 (= 1.4.0-2), python3-tk (= 3.13.5-1), python3-tornado (= 6.4.2-3), python3-traitlets (= 5.14.3+really5.14.3-1), python3-typeguard (= 4.4.4-1), python3-typeshed (= 0.0~git20241223.ea91db2-3), python3-typing-extensions (= 4.15.0-1), python3-tzlocal (= 5.3.1-1), python3-ufolib2 (= 0.17.1+dfsg1-1), python3-urllib3 (= 2.5.0-1), python3-wcwidth (= 0.2.13+dfsg1-1), python3-webencodings (= 0.5.1-5), python3-wheel (= 0.46.1-2), python3-yaml (= 6.0.2-2), python3-yapf (= 0.43.0-1), python3-zipp (= 3.21.0-1), python3-zmq (= 26.4.0-1), python3-zopfli (= 0.2.3.post1-1+b1), python3.13 (= 3.13.7-1), python3.13-dev (= 3.13.7-1), python3.13-doc (= 3.13.7-1), python3.13-minimal (= 3.13.7-1), python3.13-tk (= 3.13.7-1), r-base-core (= 4.5.1-1), r-cran-backports (= 1.5.0-2), r-cran-boot (= 1.3-31-1), r-cran-broom (= 1.0.7+dfsg-1), r-cran-cardata (= 3.0.5-1), r-cran-cli (= 3.6.4-1), r-cran-colorspace (= 2.1-1+dfsg-1), r-cran-cpp11 (= 0.5.2-1), r-cran-deoptimr (= 1.1-4-1), r-cran-dplyr (= 1.1.4-4), r-cran-fansi (= 1.0.6-2), r-cran-geepack (= 1.3.12-1), r-cran-generics (= 0.1.3-1), r-cran-glue (= 1.8.0-1), r-cran-guerry (= 1.8.3-1), r-cran-lattice (= 0.22-7-1), r-cran-lifecycle (= 1.0.4+dfsg-1), r-cran-littler (= 0.3.21-1), r-cran-lme4 (= 1.1-37-1), r-cran-lmtest (= 0.9.40-1), r-cran-magrittr (= 2.0.3-1), r-cran-mass (= 7.3-65-1), r-cran-matrix (= 1.7-4-1), r-cran-minqa (= 1.2.8-1), r-cran-nlme (= 3.1.168-1), r-cran-nloptr (= 2.2.1-2), r-cran-pillar (= 1.10.1+dfsg-1), r-cran-pkgconfig (= 2.0.3-2), r-cran-pkgkitten (= 0.2.4-1), r-cran-purrr (= 1.0.4-1), r-cran-r6 (= 2.6.1-1), r-cran-rbibutils (= 2.3-1), r-cran-rcpp (= 1.1.0-1), r-cran-rcppeigen (= 0.3.4.0.2-1), r-cran-rdpack (= 2.6.3-1), r-cran-reformulas (= 0.4.1-1), r-cran-rlang (= 1.1.5-3), r-cran-robustbase (= 0.99-4-1-1), r-cran-sp (= 1:2.2-0+dfsg-1), r-cran-statmod (= 1.5.0-1), r-cran-stringi (= 1.8.4-1+b1), r-cran-stringr (= 1.5.1-1), r-cran-tibble (= 3.2.1+dfsg-3), r-cran-tidyr (= 1.3.1-1), r-cran-tidyselect (= 1.2.1+dfsg-1), r-cran-utf8 (= 1.2.4-1), r-cran-vcd (= 1:1.4-13-1), r-cran-vctrs (= 0.6.5-1), r-cran-withr (= 3.0.2+dfsg-1), r-cran-zoo (= 1.8-14-1), readline-common (= 8.3-2), rpcsvc-proto (= 1.4.3-1), sed (= 4.9-2), sensible-utils (= 0.0.26), sgml-base (= 1.31+nmu1), sphinx-common (= 8.2.3-2), sysvinit-utils (= 3.14-4), tar (= 1.35+dfsg-3.1), tk8.6-blt2.5 (= 2.5.3+dfsg-8), tzdata (= 2025b-5), ucf (= 3.0052), unicode-data (= 15.1.0-1), unzip (= 6.0-29), util-linux (= 2.41.1-1), x11-common (= 1:7.7+24), xdg-utils (= 1.2.1-2), xml-core (= 0.19), xz-utils (= 5.8.1-1), zip (= 3.0-15), zlib1g (= 1:1.3.dfsg+really1.3.1-1+b1), zlib1g-dev (= 1:1.3.dfsg+really1.3.1-1+b1) Environment: DEB_BUILD_OPTIONS="parallel=6" LANG="C.UTF-8" LC_COLLATE="C.UTF-8" LC_CTYPE="C.UTF-8" SOURCE_DATE_EPOCH="1754831627" +------------------------------------------------------------------------------+ | Package contents Thu, 02 Oct 2025 09:25:52 +0000 | +------------------------------------------------------------------------------+ python-statsmodels-doc_0.14.5+dfsg-1_all.deb -------------------------------------------- new Debian package, version 2.0. size 51933768 bytes: control archive=334700 bytes. 1227 bytes, 23 lines control 2128619 bytes, 13777 lines md5sums 406 bytes, 6 lines * postinst #!/bin/sh 406 bytes, 6 lines * postrm #!/bin/sh 406 bytes, 6 lines * preinst #!/bin/sh 406 bytes, 6 lines * prerm #!/bin/sh Package: python-statsmodels-doc Source: statsmodels Version: 0.14.5+dfsg-1 Architecture: all Maintainer: Debian Science Maintainers Installed-Size: 172241 Depends: libjs-sphinxdoc (>= 8.2), libjs-requirejs, libjs-mathjax Suggests: python3-statsmodels, python3-doc, python-numpy-doc, python-patsy-doc, python-pandas-doc, python-scipy-doc Breaks: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc, python-statsmodels (<< 0.9.0-3~) Replaces: python-scikits-statsmodels-doc, python-scikits.statsmodels-doc, python-statsmodels (<< 0.9.0-3~) Section: doc Priority: optional Homepage: https://www.statsmodels.org Description: documentation and examples for statsmodels Statsmodels Python modules are providing classes and functions for the estimation of several categories of statistical models. These currently include linear regression models, OLS, GLS, WLS and GLS with AR(p) errors, generalized linear models for several distribution families and M-estimators for robust linear models. An extensive list of result statistics are available for each estimation problem. . 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root/root 92978 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/mixed_lm_example.ipynb.gz -rw-r--r-- root/root 44594 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/mstl_decomposition.html lrwxrwxrwx root/root 0 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/mstl_decomposition.ipynb -> ../../../../examples/notebooks/mstl_decomposition.ipynb -rw-r--r-- root/root 60938 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/ols.html -rw-r--r-- root/root 95566 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/ols.ipynb.gz -rw-r--r-- root/root 50631 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/ordinal_regression.html lrwxrwxrwx root/root 0 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/ordinal_regression.ipynb -> ../../../../examples/notebooks/ordinal_regression.ipynb -rw-r--r-- root/root 39581 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/pca_fertility_factors.html -rw-r--r-- root/root 350185 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/pca_fertility_factors.ipynb.gz -rw-r--r-- root/root 46200 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/plots_boxplots.html -rw-r--r-- root/root 1281901 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/plots_boxplots.ipynb.gz -rw-r--r-- root/root 81065 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/postestimation_poisson.html -rw-r--r-- root/root 523727 2025-08-10 13:13 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./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_custom_models.ipynb -> ../../../../examples/notebooks/statespace_custom_models.ipynb -rw-r--r-- root/root 24120 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_cycles.html lrwxrwxrwx root/root 0 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_cycles.ipynb -> ../../../../examples/notebooks/statespace_cycles.ipynb -rw-r--r-- root/root 87436 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_dfm_coincident.html lrwxrwxrwx root/root 0 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_dfm_coincident.ipynb -> ../../../../examples/notebooks/statespace_dfm_coincident.ipynb -rw-r--r-- root/root 29973 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_fixed_params.html lrwxrwxrwx root/root 0 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_fixed_params.ipynb -> ../../../../examples/notebooks/statespace_fixed_params.ipynb -rw-r--r-- root/root 79051 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_forecasting.html -rw-r--r-- root/root 106430 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_forecasting.ipynb.gz -rw-r--r-- root/root 35138 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_local_linear_trend.html lrwxrwxrwx root/root 0 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_local_linear_trend.ipynb -> ../../../../examples/notebooks/statespace_local_linear_trend.ipynb -rw-r--r-- root/root 66879 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_news.html lrwxrwxrwx root/root 0 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_news.ipynb -> ../../../../examples/notebooks/statespace_news.ipynb -rw-r--r-- root/root 80915 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_sarimax_faq.html lrwxrwxrwx root/root 0 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_sarimax_faq.ipynb -> ../../../../examples/notebooks/statespace_sarimax_faq.ipynb -rw-r--r-- root/root 27702 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_sarimax_internet.html lrwxrwxrwx root/root 0 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_sarimax_internet.ipynb -> ../../../../examples/notebooks/statespace_sarimax_internet.ipynb -rw-r--r-- root/root 59589 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_sarimax_pymc3.html lrwxrwxrwx root/root 0 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_sarimax_pymc3.ipynb -> ../../../../examples/notebooks/statespace_sarimax_pymc3.ipynb -rw-r--r-- root/root 72003 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_sarimax_stata.html lrwxrwxrwx root/root 0 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_sarimax_stata.ipynb -> ../../../../examples/notebooks/statespace_sarimax_stata.ipynb -rw-r--r-- root/root 73306 2025-08-10 13:13 ./usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/statespace_seasonal.html -rw-r--r-- root/root 1313434 2025-08-10 13:13 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2025-07-07 10:23 ./usr/share/doc/python-statsmodels-doc/html/versions-v3.json drwxr-xr-x root/root 0 2025-08-10 13:13 ./usr/share/doc/python3-statsmodels/ lrwxrwxrwx root/root 0 2025-08-10 13:13 ./usr/share/doc/python3-statsmodels/examples -> ../python-statsmodels-doc/examples lrwxrwxrwx root/root 0 2025-08-10 13:13 ./usr/share/doc/python3-statsmodels/html -> ../python-statsmodels-doc/html python3-statsmodels_0.14.5+dfsg-1_all.deb ----------------------------------------- new Debian package, version 2.0. size 4826544 bytes: control archive=32736 bytes. 1067 bytes, 19 lines control 157906 bytes, 1376 lines md5sums 273 bytes, 12 lines * postinst #!/bin/sh 386 bytes, 12 lines * prerm #!/bin/sh Package: python3-statsmodels Source: statsmodels Version: 0.14.5+dfsg-1 Architecture: all Maintainer: Debian Science Maintainers Installed-Size: 24559 Depends: python3-numpy (>= 1:2.0.0~), python3-packaging (>= 21.3~), python3-pandas (>= 1.4~), python3-patsy (>= 0.5.6~), python3-scipy (>= 1.13~), python3:any, python3-statsmodels-lib (>= 0.14.5+dfsg-1) Recommends: python3-matplotlib, python3-joblib, python3-colorama, python3-cvxopt Suggests: python-statsmodels-doc Section: python Priority: optional Homepage: https://www.statsmodels.org Description: Python3 module for the estimation of statistical models statsmodels Python3 module provides classes and functions for the estimation of several categories of statistical models. These currently include linear regression models, OLS, GLS, WLS and GLS with AR(p) errors, generalized linear models for several distribution families and M-estimators for robust linear models. 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+------------------------------------------------------------------------------+ | Summary Thu, 02 Oct 2025 09:25:59 +0000 | +------------------------------------------------------------------------------+ Build Architecture: amd64 Build Type: all Build-Space: 1184668 Build-Time: 2777 Distribution: unstable Host Architecture: amd64 Install-Time: 4 Job: /srv/rebuilderd/tmp/rebuilderdrdSFyz/inputs/statsmodels_0.14.5+dfsg-1.dsc Machine Architecture: amd64 Package: statsmodels Package-Time: 2805 Source-Version: 0.14.5+dfsg-1 Space: 1184668 Status: successful Version: 0.14.5+dfsg-1 -------------------------------------------------------------------------------- Finished at 2025-10-02T09:25:51Z Build needed 00:46:45, 1184668k disk space build artifacts stored in /srv/rebuilderd/tmp/rebuilderdrdSFyz/out checking python-statsmodels-doc_0.14.5+dfsg-1_all.deb: size differs for python-statsmodels-doc_0.14.5+dfsg-1_all.deb