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Similarity: 0.999729316009558% Differences: {"'cells'": "{26: {'outputs': {1: {'text': {insert: [(22, " "'==============================================================================')], " "delete: [22]}}, insert: [(2, OrderedDict({'name': 'stdout', 'output_type': 'stream', " "'text': ['\\n']}))]}}, 28: {'outputs': {0: {'name': 'stderr', 'text': " "['/usr/lib/python3/dist-packages/statsmodels/base/model.py:607: ConvergenceWarning: " "Maximum Likelihood optimization failed to converge. Chec […]

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1	-rw-r--r--···0········0········0········4·2025-08-10·13:13:47.000000·debian-binary	1	-rw-r--r--···0········0········0········4·2025-08-10·13:13:47.000000·debian-binary
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1	Package:·python-statsmodels-doc	1	Package:·python-statsmodels-doc
2	Source:·statsmodels	2	Source:·statsmodels
3	Version:·0.14.5+dfsg-1	3	Version:·0.14.5+dfsg-1
4	Architecture:·all	4	Architecture:·all
5	Maintainer:·Debian·Science·Maintainers·<debian-science-maintainers@lists.alioth.debian.org>	5	Maintainer:·Debian·Science·Maintainers·<debian-science-maintainers@lists.alioth.debian.org>
6	Installed-Size:·172472	6	Installed-Size:·172450
7	Depends:·libjs-sphinxdoc·(>=·8.2),·libjs-requirejs,·libjs-mathjax	7	Depends:·libjs-sphinxdoc·(>=·8.2),·libjs-requirejs,·libjs-mathjax
8	Suggests:·python3-statsmodels,·python3-doc,·python-numpy-doc,·python-patsy-doc,·python-pandas-doc,·python-scipy-doc	8	Suggests:·python3-statsmodels,·python3-doc,·python-numpy-doc,·python-patsy-doc,·python-pandas-doc,·python-scipy-doc
9	Breaks:·python-scikits-statsmodels-doc,·python-scikits.statsmodels-doc,·python-statsmodels·(<<·0.9.0-3~)	9	Breaks:·python-scikits-statsmodels-doc,·python-scikits.statsmodels-doc,·python-statsmodels·(<<·0.9.0-3~)
10	Replaces:·python-scikits-statsmodels-doc,·python-scikits.statsmodels-doc,·python-statsmodels·(<<·0.9.0-3~)	10	Replaces:·python-scikits-statsmodels-doc,·python-scikits.statsmodels-doc,·python-statsmodels·(<<·0.9.0-3~)
11	Section:·doc	11	Section:·doc
12	Priority:·optional	12	Priority:·optional
13	Homepage:·https://www.statsmodels.org	13	Homepage:·https://www.statsmodels.org


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1003	usr/share/doc/python-statsmodels-doc/html/_sources/examples/notebooks/generated/stats_rankcompare.ipynb.txt	1003	usr/share/doc/python-statsmodels-doc/html/_sources/examples/notebooks/generated/stats_rankcompare.ipynb.txt
1004	usr/share/doc/python-statsmodels-doc/html/_sources/examples/notebooks/generated/stl_decomposition.ipynb.txt	1004	usr/share/doc/python-statsmodels-doc/html/_sources/examples/notebooks/generated/stl_decomposition.ipynb.txt
1005	usr/share/doc/python-statsmodels-doc/html/_sources/examples/notebooks/generated/treatment_effect.ipynb.txt	1005	usr/share/doc/python-statsmodels-doc/html/_sources/examples/notebooks/generated/treatment_effect.ipynb.txt
1006	usr/share/doc/python-statsmodels-doc/html/_sources/examples/notebooks/generated/tsa_arma_0.ipynb.txt	1006	usr/share/doc/python-statsmodels-doc/html/_sources/examples/notebooks/generated/tsa_arma_0.ipynb.txt
1007	usr/share/doc/python-statsmodels-doc/html/_sources/examples/notebooks/generated/tsa_arma_1.ipynb.txt	1007	usr/share/doc/python-statsmodels-doc/html/_sources/examples/notebooks/generated/tsa_arma_1.ipynb.txt
1008	usr/share/doc/python-statsmodels-doc/html/_sources/examples/notebooks/generated/tsa_dates.ipynb.txt	1008	usr/share/doc/python-statsmodels-doc/html/_sources/examples/notebooks/generated/tsa_dates.ipynb.txt
1009	usr/share/doc/python-statsmodels-doc/html/_sources/examples/notebooks/generated/tsa_filters.ipynb.txt	1009	usr/share/doc/python-statsmodels-doc/html/_sources/examples/notebooks/generated/tsa_filters.ipynb.txt
1010	usr/share/doc/python-statsmodels-doc/html/_sources/examples/notebooks/generated/variance_components.ipynb.txt
1011	usr/share/doc/python-statsmodels-doc/html/_sources/examples/notebooks/generated/wls.ipynb.txt	1010	usr/share/doc/python-statsmodels-doc/html/_sources/examples/notebooks/generated/wls.ipynb.txt
1012	usr/share/doc/python-statsmodels-doc/html/_sources/faq.rst.txt	1011	usr/share/doc/python-statsmodels-doc/html/_sources/faq.rst.txt
1013	usr/share/doc/python-statsmodels-doc/html/_sources/gam.rst.txt	1012	usr/share/doc/python-statsmodels-doc/html/_sources/gam.rst.txt
1014	usr/share/doc/python-statsmodels-doc/html/_sources/gee.rst.txt	1013	usr/share/doc/python-statsmodels-doc/html/_sources/gee.rst.txt
1015	usr/share/doc/python-statsmodels-doc/html/_sources/generated/statsmodels.base.distributed_estimation.DistributedModel.fit.rst.txt	1014	usr/share/doc/python-statsmodels-doc/html/_sources/generated/statsmodels.base.distributed_estimation.DistributedModel.fit.rst.txt
1016	usr/share/doc/python-statsmodels-doc/html/_sources/generated/statsmodels.base.distributed_estimation.DistributedModel.fit_joblib.rst.txt	1015	usr/share/doc/python-statsmodels-doc/html/_sources/generated/statsmodels.base.distributed_estimation.DistributedModel.fit_joblib.rst.txt
1017	usr/share/doc/python-statsmodels-doc/html/_sources/generated/statsmodels.base.distributed_estimation.DistributedModel.fit_sequential.rst.txt	1016	usr/share/doc/python-statsmodels-doc/html/_sources/generated/statsmodels.base.distributed_estimation.DistributedModel.fit_sequential.rst.txt
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7565	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/tsa_arma_1.html	7564	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/tsa_arma_1.html
7566	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/tsa_arma_1.ipynb.gz	7565	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/tsa_arma_1.ipynb.gz
7567	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/tsa_dates.html	7566	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/tsa_dates.html
7568	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/tsa_dates.ipynb.gz	7567	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/tsa_dates.ipynb.gz
7569	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/tsa_filters.html	7568	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/tsa_filters.html
7570	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/tsa_filters.ipynb.gz	7569	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/tsa_filters.ipynb.gz
7571	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/variance_components.html	7570	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/variance_components.html
7572	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/variance_components.ipynb.gz
7573	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/wls.html	7571	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/wls.html
7574	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/wls.ipynb.gz	7572	usr/share/doc/python-statsmodels-doc/html/examples/notebooks/generated/wls.ipynb.gz
7575	usr/share/doc/python-statsmodels-doc/html/faq.html	7573	usr/share/doc/python-statsmodels-doc/html/faq.html
7576	usr/share/doc/python-statsmodels-doc/html/gam.html	7574	usr/share/doc/python-statsmodels-doc/html/gam.html
7577	usr/share/doc/python-statsmodels-doc/html/gee.html	7575	usr/share/doc/python-statsmodels-doc/html/gee.html
7578	usr/share/doc/python-statsmodels-doc/html/generated/statsmodels.base.distributed_estimation.DistributedModel.fit.html	7576	usr/share/doc/python-statsmodels-doc/html/generated/statsmodels.base.distributed_estimation.DistributedModel.fit.html
7579	usr/share/doc/python-statsmodels-doc/html/generated/statsmodels.base.distributed_estimation.DistributedModel.fit_joblib.html	7577	usr/share/doc/python-statsmodels-doc/html/generated/statsmodels.base.distributed_estimation.DistributedModel.fit_joblib.html


Offset 477, 15 lines modified		Offset 477, 22 lines modified
477	························"fmde··········-0.0346······0.002····-21.439······0.000······-0.038······-0.031\n",	477	························"fmde··········-0.0346······0.002····-21.439······0.000······-0.038······-0.031\n",
478	························"physlm·········0.2717······0.012·····22.200······0.000·······0.248·······0.296\n",	478	························"physlm·········0.2717······0.012·····22.200······0.000·······0.248·······0.296\n",
479	························"disea··········0.0339······0.001·····60.098······0.000·······0.033·······0.035\n",	479	························"disea··········0.0339······0.001·····60.098······0.000·······0.033·······0.035\n",
480	························"hlthg·········-0.0126······0.009·····-1.366······0.172······-0.031·······0.005\n",	480	························"hlthg·········-0.0126······0.009·····-1.366······0.172······-0.031·······0.005\n",
481	························"hlthf··········0.0541······0.015······3.531······0.000·······0.024·······0.084\n",	481	························"hlthf··········0.0541······0.015······3.531······0.000·······0.024·······0.084\n",
482	························"hlthp··········0.2061······0.026······7.843······0.000·······0.155·······0.258\n",	482	························"hlthp··········0.2061······0.026······7.843······0.000·······0.155·······0.258\n",
483	························"const··········0.7004······0.011·····62.741······0.000·······0.678·······0.722\n",	483	························"const··········0.7004······0.011·····62.741······0.000·······0.678·······0.722\n",
484	························"==============================================================================\n"	484	························"=============================================================================="
		485	····················]
		486	················},
		487	················{
		488	····················"name":·"stdout",
		489	····················"output_type":·"stream",
		490	····················"text":·[
		491	························"\n"
485	····················]	492	····················]
486	················}	493	················}
487	············],	494	············],
488	············"source":·[	495	············"source":·[
489	················"poisson_mod·=·sm.Poisson(rand_data.endog,·rand_exog)\n",	496	················"poisson_mod·=·sm.Poisson(rand_data.endog,·rand_exog)\n",
490	················"poisson_res·=·poisson_mod.fit(method=\"newton\")\n",	497	················"poisson_res·=·poisson_mod.fit(method=\"newton\")\n",
491	················"print(poisson_res.summary())"	498	················"print(poisson_res.summary())"
Offset 507, 14 lines modified		Offset 514, 22 lines modified
507	················"execution":·{},	514	················"execution":·{},
508	················"jupyter":·{	515	················"jupyter":·{
509	····················"outputs_hidden":·false	516	····················"outputs_hidden":·false
510	················}	517	················}
511	············},	518	············},
512	············"outputs":·[	519	············"outputs":·[
513	················{	520	················{
		521	····················"name":·"stderr",
		522	····················"output_type":·"stream",
		523	····················"text":·[
		524	························"/usr/lib/python3/dist-packages/statsmodels/base/model.py:607:·ConvergenceWarning:·Maximum·Likelihood·optimization·failed·to·converge.·Check·mle_retvals\n",
		525	························"··warnings.warn(\"Maximum·Likelihood·optimization·failed·to·\"\n"
		526	····················]
		527	················},
		528	················{
514	····················"name":·"stdout",	529	····················"name":·"stdout",
515	····················"output_type":·"stream",	530	····················"output_type":·"stream",
516	····················"text":·[	531	····················"text":·[
517	························"·····················NegativeBinomial·Regression·Results······················\n",	532	························"·····················NegativeBinomial·Regression·Results······················\n",
518	························"==============================================================================\n",	533	························"==============================================================================\n",
519	························"Dep.·Variable:··················mdvis···No.·Observations:················20190\n",	534	························"Dep.·Variable:··················mdvis···No.·Observations:················20190\n",
520	························"Model:···············NegativeBinomial···Df·Residuals:····················20180\n",	535	························"Model:···············NegativeBinomial···Df·Residuals:····················20180\n",
Offset 535, 22 lines modified		Offset 550, 14 lines modified
535	························"hlthg·········-0.0441······0.020·····-2.201······0.028······-0.083······-0.005\n",	550	························"hlthg·········-0.0441······0.020·····-2.201······0.028······-0.083······-0.005\n",
536	························"hlthf··········0.0173······0.036······0.478······0.632······-0.054·······0.088\n",	551	························"hlthf··········0.0173······0.036······0.478······0.632······-0.054·······0.088\n",
537	························"hlthp··········0.1782······0.074······2.399······0.016·······0.033·······0.324\n",	552	························"hlthp··········0.1782······0.074······2.399······0.016·······0.033·······0.324\n",
538	························"const··········0.6635······0.025·····26.786······0.000·······0.615·······0.712\n",	553	························"const··········0.6635······0.025·····26.786······0.000·······0.615·······0.712\n",
539	························"alpha··········1.2930······0.019·····69.477······0.000·······1.256·······1.329\n",	554	························"alpha··········1.2930······0.019·····69.477······0.000·······1.256·······1.329\n",
540	························"==============================================================================\n"	555	························"==============================================================================\n"
541	····················]	556	····················]
542	················},
543	················{
544	····················"name":·"stderr",
545	····················"output_type":·"stream",
546	····················"text":·[
547	························"/usr/lib/python3/dist-packages/statsmodels/base/model.py:607:·ConvergenceWarning:·Maximum·Likelihood·optimization·failed·to·converge.·Check·mle_retvals\n",
548	························"··warnings.warn(\"Maximum·Likelihood·optimization·failed·to·\"\n"
549	····················]
550	················}	557	················}
551	············],	558	············],
552	············"source":·[	559	············"source":·[
553	················"mod_nbin·=·sm.NegativeBinomial(rand_data.endog,·rand_exog)\n",	560	················"mod_nbin·=·sm.NegativeBinomial(rand_data.endog,·rand_exog)\n",
554	················"res_nbin·=·mod_nbin.fit(disp=False)\n",	561	················"res_nbin·=·mod_nbin.fit(disp=False)\n",
555	················"print(res_nbin.summary())"	562	················"print(res_nbin.summary())"
556	············]	563	············]


Offset 162, 21 lines modified		Offset 162, 15 lines modified
162	················{	162	················{
163	····················"name":·"stdout",	163	····················"name":·"stdout",
164	····················"output_type":·"stream",	164	····················"output_type":·"stream",
165	····················"text":·[	165	····················"text":·[
166	························"Optimization·terminated·successfully.\n",	166	························"Optimization·terminated·successfully.\n",
167	························"·········Current·function·value:·0.400588\n",	167	························"·········Current·function·value:·0.400588\n",
168	························"·········Iterations:·292\n",	168	························"·········Iterations:·292\n",
169	························"·········Function·evaluations:·494\n"	169	························"·········Function·evaluations:·494\n",
170	····················]
171	················},
172	················{
173	····················"name":·"stdout",
174	····················"output_type":·"stream",
175	····················"text":·[
176	························"·······························MyProbit·Results·······························\n",	170	························"·······························MyProbit·Results·······························\n",
177	························"==============================================================================\n",	171	························"==============================================================================\n",
178	························"Dep.·Variable:··················GRADE···Log-Likelihood:················-12.819\n",	172	························"Dep.·Variable:··················GRADE···Log-Likelihood:················-12.819\n",
179	························"Model:·······················MyProbit···AIC:·····························33.64\n",	173	························"Model:·······················MyProbit···AIC:·····························33.64\n",
180	························"Method:············Maximum·Likelihood···BIC:·····························39.50\n",	174	························"Method:············Maximum·Likelihood···BIC:·····························39.50\n",
181	························"Date:················Sun,·10·Aug·2025·········································\n",	175	························"Date:················Sun,·10·Aug·2025·········································\n",
182	························"Time:························13:13:47·········································\n",	176	························"Time:························13:13:47·········································\n",


Offset 1170, 15 lines modified		Offset 1170, 22 lines modified
1170	························"=================================================================================\n",	1170	························"=================================================================================\n",
1171	························"····················coef····std·err··········z······P>\|z\|······[0.025······0.975]\n",	1171	························"····················coef····std·err··········z······P>\|z\|······[0.025······0.975]\n",
1172	························"---------------------------------------------------------------------------------\n",	1172	························"---------------------------------------------------------------------------------\n",
1173	························"Intercept·········2.7155······0.107·····25.294······0.000·······2.505·······2.926\n",	1173	························"Intercept·········2.7155······0.107·····25.294······0.000·······2.505·······2.926\n",
1174	························"rate_marriage····-0.4952······0.012····-41.702······0.000······-0.518······-0.472\n",	1174	························"rate_marriage····-0.4952······0.012····-41.702······0.000······-0.518······-0.472\n",
1175	························"age··············-0.0299······0.004·····-6.691······0.000······-0.039······-0.021\n",	1175	························"age··············-0.0299······0.004·····-6.691······0.000······-0.039······-0.021\n",
1176	························"yrs_married······-0.0108······0.004·····-2.507······0.012······-0.019······-0.002\n",	1176	························"yrs_married······-0.0108······0.004·····-2.507······0.012······-0.019······-0.002\n",
1177	························"=================================================================================\n"	1177	························"================================================================================="
		1178	····················]
		1179	················},
		1180	················{
		1181	····················"name":·"stdout",
		1182	····················"output_type":·"stream",
		1183	····················"text":·[
		1184	························"\n"
1178	····················]	1185	····················]
1179	················}	1186	················}
1180	············],	1187	············],
1181	············"source":·[	1188	············"source":·[
1182	················"glm·=·smf.glm(\n",	1189	················"glm·=·smf.glm(\n",
1183	················"····\"affairs_sum·~·rate_marriage·+·age·+·yrs_married\",\n",	1190	················"····\"affairs_sum·~·rate_marriage·+·age·+·yrs_married\",\n",
1184	················"····data=df_a,\n",	1191	················"····data=df_a,\n",
Offset 1251, 15 lines modified		Offset 1258, 22 lines modified
1251	························"=================================================================================\n",	1258	························"=================================================================================\n",
1252	························"····················coef····std·err··········z······P>\|z\|······[0.025······0.975]\n",	1259	························"····················coef····std·err··········z······P>\|z\|······[0.025······0.975]\n",
1253	························"---------------------------------------------------------------------------------\n",	1260	························"---------------------------------------------------------------------------------\n",
1254	························"Intercept·········2.7155······0.107·····25.294······0.000·······2.505·······2.926\n",	1261	························"Intercept·········2.7155······0.107·····25.294······0.000·······2.505·······2.926\n",
1255	························"rate_marriage····-0.4952······0.012····-41.702······0.000······-0.518······-0.472\n",	1262	························"rate_marriage····-0.4952······0.012····-41.702······0.000······-0.518······-0.472\n",
1256	························"age··············-0.0299······0.004·····-6.691······0.000······-0.039······-0.021\n",	1263	························"age··············-0.0299······0.004·····-6.691······0.000······-0.039······-0.021\n",
1257	························"yrs_married······-0.0108······0.004·····-2.507······0.012······-0.019······-0.002\n",	1264	························"yrs_married······-0.0108······0.004·····-2.507······0.012······-0.019······-0.002\n",
1258	························"=================================================================================\n"	1265	························"================================================================================="
		1266	····················]
		1267	················},
		1268	················{
		1269	····················"name":·"stdout",
		1270	····················"output_type":·"stream",
		1271	····················"text":·[
		1272	························"\n"
1259	····················]	1273	····················]
1260	················}	1274	················}
1261	············],	1275	············],
1262	············"source":·[	1276	············"source":·[
1263	················"glm·=·smf.glm(\n",	1277	················"glm·=·smf.glm(\n",
1264	················"····\"affairs_mean·~·rate_marriage·+·age·+·yrs_married\",\n",	1278	················"····\"affairs_mean·~·rate_marriage·+·age·+·yrs_married\",\n",
1265	················"····data=df_a,\n",	1279	················"····data=df_a,\n",


Offset 1531, 22 lines modified		Offset 1531, 15 lines modified
1531	························"truck.driver············-0.129227··0.897810···0.999436\n",	1531	························"truck.driver············-0.129227··0.897810···0.999436\n",
1532	························"cook·····················0.127207··0.899399···0.999436\n",	1532	························"cook·····················0.127207··0.899399···0.999436\n",
1533	························"janitor·················-0.079890··0.936713···0.999436\n",	1533	························"janitor·················-0.079890··0.936713···0.999436\n",
1534	························"policeman················0.078847··0.937538···0.999436\n",	1534	························"policeman················0.078847··0.937538···0.999436\n",
1535	························"architect················0.072256··0.942750···0.999436\n",	1535	························"architect················0.072256··0.942750···0.999436\n",
1536	························"teacher··················0.050510··0.959961···0.999436\n",	1536	························"teacher··················0.050510··0.959961···0.999436\n",
1537	························"taxi.driver··············0.023322··0.981507···0.999436\n",	1537	························"taxi.driver··············0.023322··0.981507···0.999436\n",
1538	························"author···················0.000711··0.999436···0.999436"	1538	························"author···················0.000711··0.999436···0.999436\n"
1539	····················]
1540	················},
1541	················{
1542	····················"name":·"stdout",
1543	····················"output_type":·"stream",
1544	····················"text":·[
1545	························"\n"
1546	····················]	1539	····················]
1547	················}	1540	················}
1548	············],	1541	············],
1549	············"source":·[	1542	············"source":·[
1550	················"fdr·=·ols_model.outlier_test(\"fdr_bh\")\n",	1543	················"fdr·=·ols_model.outlier_test(\"fdr_bh\")\n",
1551	················"fdr.sort_values(\"unadj_p\",·inplace=True)\n",	1544	················"fdr.sort_values(\"unadj_p\",·inplace=True)\n",
1552	················"print(fdr)"	1545	················"print(fdr)"
Offset 1578, 15 lines modified		Offset 1571, 22 lines modified
1578	························"·················coef····std·err··········z······P>\|z\|······[0.025······0.975]\n",	1571	························"·················coef····std·err··········z······P>\|z\|······[0.025······0.975]\n",
1579	························"------------------------------------------------------------------------------\n",	1572	························"------------------------------------------------------------------------------\n",
1580	························"Intercept·····-7.1107······3.879·····-1.833······0.067·····-14.713·······0.492\n",	1573	························"Intercept·····-7.1107······3.879·····-1.833······0.067·····-14.713·······0.492\n",
1581	························"income·········0.7015······0.109······6.456······0.000·······0.489·······0.914\n",	1574	························"income·········0.7015······0.109······6.456······0.000·······0.489·······0.914\n",
1582	························"education······0.4854······0.089······5.441······0.000·······0.311·······0.660\n",	1575	························"education······0.4854······0.089······5.441······0.000·······0.311·······0.660\n",
1583	························"==============================================================================\n",	1576	························"==============================================================================\n",
1584	························"\n",	1577	························"\n",
1585	························"If·the·model·instance·has·been·used·for·another·fit·with·different·fit·parameters,·then·the·fit·options·might·not·be·the·correct·ones·anymore·.\n"	1578	························"If·the·model·instance·has·been·used·for·another·fit·with·different·fit·parameters,·then·the·fit·options·might·not·be·the·correct·ones·anymore·."
		1579	····················]
		1580	················},
		1581	················{
		1582	····················"name":·"stdout",
		1583	····················"output_type":·"stream",
		1584	····················"text":·[
		1585	························"\n"
1586	····················]	1586	····················]
1587	················}	1587	················}
1588	············],	1588	············],
1589	············"source":·[	1589	············"source":·[
1590	················"rlm_model·=·rlm(\"prestige·~·income·+·education\",·prestige).fit()\n",	1590	················"rlm_model·=·rlm(\"prestige·~·income·+·education\",·prestige).fit()\n",
1591	················"print(rlm_model.summary())"	1591	················"print(rlm_model.summary())"
1592	············]	1592	············]
Offset 1643, 22 lines modified		Offset 1643, 15 lines modified
1643	························"shoe.shiner···········1.000000\n",	1643	························"shoe.shiner···········1.000000\n",
1644	························"cook··················1.000000\n",	1644	························"cook··················1.000000\n",
1645	························"soda.clerk············1.000000\n",	1645	························"soda.clerk············1.000000\n",
1646	························"watchman··············1.000000\n",	1646	························"watchman··············1.000000\n",
1647	························"janitor···············1.000000\n",	1647	························"janitor···············1.000000\n",
1648	························"policeman·············1.000000\n",	1648	························"policeman·············1.000000\n",
1649	························"waiter················1.000000\n",	1649	························"waiter················1.000000\n",
1650	························"dtype:·float64"	1650	························"dtype:·float64\n"
1651	····················]
1652	················},
1653	················{
1654	····················"name":·"stdout",
1655	····················"output_type":·"stream",
1656	····················"text":·[
1657	························"\n"
1658	····················]	1651	····················]
1659	················}	1652	················}
1660	············],	1653	············],
1661	············"source":·[	1654	············"source":·[
1662	················"print(rlm_model.weights)"	1655	················"print(rlm_model.weights)"
1663	············]	1656	············]
1664	········},	1657	········},


Offset 609, 15 lines modified		Offset 609, 21 lines modified
609	························"···cond-midp····0.0005572624066190538\n",	609	························"···cond-midp····0.0005572624066190538\n",
610	························"···sqrt·········0.0005700355621795108\n",	610	························"···sqrt·········0.0005700355621795108\n",
611	························"···etest-score··0.0005672617581627985\n",	611	························"···etest-score··0.0005672617581627985\n",
612	························"···etest-wald···0.000643144612489785\n",	612	························"···etest-wald···0.000643144612489785\n",
613	························"diff\n",	613	························"diff\n",
614	························"···wald·········0.0007120093285061094\n",	614	························"···wald·········0.0007120093285061094\n",
615	························"···score········0.0006322188820470941\n",	615	························"···score········0.0006322188820470941\n",
616	························"···waldccv······0.0007610462660136598\n",	616	························"···waldccv······0.0007610462660136598\n"
		617	····················]
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617	························"···etest-score··0.0005672617581627926\n",	623	························"···etest-score··0.0005672617581627926\n",
618	························"···etest-wald···0.0006431446124897783\n"	624	························"···etest-wald···0.0006431446124897783\n"
619	····················]	625	····················]
620	················}	626	················}
621	············],	627	············],
622	············"source":·[	628	············"source":·[
623	················"for·compare·in·[\"ratio\",·\"diff\"]:\n",	629	················"for·compare·in·[\"ratio\",·\"diff\"]:\n",


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Offset 407, 14 lines modified		Offset 407, 23 lines modified
407	<span·class="nb">print</span><span·class="p">(</span><span·class="n">res_nbin</span><span·class="o">.</span><span·class="n">summary</span><span·class="p">())</span>	407	<span·class="nb">print</span><span·class="p">(</span><span·class="n">res_nbin</span><span·class="o">.</span><span·class="n">summary</span><span·class="p">())</span>
408	</pre></div>	408	</pre></div>
409	</div>	409	</div>
410	</div>	410	</div>
411	<div·class="nboutput·docutils·container">	411	<div·class="nboutput·docutils·container">
412	<div·class="prompt·empty·docutils·container">	412	<div·class="prompt·empty·docutils·container">
413	</div>	413	</div>
		414	<div·class="output_area·stderr·docutils·container">
		415	<div·class="highlight"><pre>
		416	/usr/lib/python3/dist-packages/statsmodels/base/model.py:607:·ConvergenceWarning:·Maximum·Likelihood·optimization·failed·to·converge.·Check·mle_retvals
		417	··warnings.warn("Maximum·Likelihood·optimization·failed·to·"
		418	</pre></div></div>
		419	</div>
		420	<div·class="nboutput·nblast·docutils·container">
		421	<div·class="prompt·empty·docutils·container">
		422	</div>
414	<div·class="output_area·docutils·container">	423	<div·class="output_area·docutils·container">
415	<div·class="highlight"><pre>	424	<div·class="highlight"><pre>
416	·····················NegativeBinomial·Regression·Results	425	·····················NegativeBinomial·Regression·Results
417	==============================================================================	426	==============================================================================
418	Dep.·Variable:··················mdvis···No.·Observations:················20190	427	Dep.·Variable:··················mdvis···No.·Observations:················20190
419	Model:···············NegativeBinomial···Df·Residuals:····················20180	428	Model:···············NegativeBinomial···Df·Residuals:····················20180
420	Method:···························MLE···Df·Model:····························9	429	Method:···························MLE···Df·Model:····························9
Offset 435, 23 lines modified		Offset 444, 14 lines modified
435	hlthf··········0.0173······0.036······0.478······0.632······-0.054·······0.088	444	hlthf··········0.0173······0.036······0.478······0.632······-0.054·······0.088
436	hlthp··········0.1782······0.074······2.399······0.016·······0.033·······0.324	445	hlthp··········0.1782······0.074······2.399······0.016·······0.033·······0.324
437	const··········0.6635······0.025·····26.786······0.000·······0.615·······0.712	446	const··········0.6635······0.025·····26.786······0.000·······0.615·······0.712
438	alpha··········1.2930······0.019·····69.477······0.000·······1.256·······1.329	447	alpha··········1.2930······0.019·····69.477······0.000·······1.256·······1.329
439	==============================================================================	448	==============================================================================
440	</pre></div></div>	449	</pre></div></div>
441	</div>	450	</div>
442	<div·class="nboutput·nblast·docutils·container">
443	<div·class="prompt·empty·docutils·container">
444	</div>
445	<div·class="output_area·stderr·docutils·container">
446	<div·class="highlight"><pre>
447	/usr/lib/python3/dist-packages/statsmodels/base/model.py:607:·ConvergenceWarning:·Maximum·Likelihood·optimization·failed·to·converge.·Check·mle_retvals
448	··warnings.warn("Maximum·Likelihood·optimization·failed·to·"
449	</pre></div></div>
450	</div>
451	</section>	451	</section>
452	<section·id="Alternative-solvers">	452	<section·id="Alternative-solvers">
453	<h2>Alternative·solvers<a·class="headerlink"·href="#Alternative-solvers"·title="Link·to·this·heading">¶</a></h2>	453	<h2>Alternative·solvers<a·class="headerlink"·href="#Alternative-solvers"·title="Link·to·this·heading">¶</a></h2>
454	<p>The·default·method·for·fitting·discrete·data·MLE·models·is·Newton-Raphson.·You·can·use·other·solvers·by·using·the·<code·class="docutils·literal·notranslate"><span·class="pre">method</span></code>·argument:</p>	454	<p>The·default·method·for·fitting·discrete·data·MLE·models·is·Newton-Raphson.·You·can·use·other·solvers·by·using·the·<code·class="docutils·literal·notranslate"><span·class="pre">method</span></code>·argument:</p>
455	<div·class="nbinput·docutils·container">	455	<div·class="nbinput·docutils·container">
456	<div·class="prompt·highlight-none·notranslate"><div·class="highlight"><pre><span></span>[15]:	456	<div·class="prompt·highlight-none·notranslate"><div·class="highlight"><pre><span></span>[15]:
457	</pre></div>	457	</pre></div>


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195	==============================================================================	195	==============================================================================
196	\x8\x8\x8\x8\x8·N\x8Ne\x8eg\x8ga\x8at\x8ti\x8iv\x8ve\x8e·B\x8Bi\x8in\x8no\x8om\x8mi\x8ia\x8al\x8l_\x8?\x8¶·\x8\x8\x8\x8\x8	196	\x8\x8\x8\x8\x8·N\x8Ne\x8eg\x8ga\x8at\x8ti\x8iv\x8ve\x8e·B\x8Bi\x8in\x8no\x8om\x8mi\x8ia\x8al\x8l_\x8?\x8¶·\x8\x8\x8\x8\x8
197	The·negative·binomial·model·gives·slightly·different·results.	197	The·negative·binomial·model·gives·slightly·different·results.
198	[14]:	198	[14]:
199	mod_nbin·=·sm.NegativeBinomial(rand_data.endog,·rand_exog)	199	mod_nbin·=·sm.NegativeBinomial(rand_data.endog,·rand_exog)
200	res_nbin·=·mod_nbin.fit(disp=False)	200	res_nbin·=·mod_nbin.fit(disp=False)
201	print(res_nbin.summary())	201	print(res_nbin.summary())
		202	/usr/lib/python3/dist-packages/statsmodels/base/model.py:607:
		203	ConvergenceWarning:·Maximum·Likelihood·optimization·failed·to·converge.·Check
		204	mle_retvals
		205	··warnings.warn("Maximum·Likelihood·optimization·failed·to·"
202	·····················NegativeBinomial·Regression·Results	206	·····················NegativeBinomial·Regression·Results
203	==============================================================================	207	==============================================================================
204	Dep.·Variable:··················mdvis···No.·Observations:················20190	208	Dep.·Variable:··················mdvis···No.·Observations:················20190
205	Model:···············NegativeBinomial···Df·Residuals:····················20180	209	Model:···············NegativeBinomial···Df·Residuals:····················20180
206	Method:···························MLE···Df·Model:····························9	210	Method:···························MLE···Df·Model:····························9
207	Date:················Sun,·10·Aug·2025···Pseudo·R-squ.:·················0.01845	211	Date:················Sun,·10·Aug·2025···Pseudo·R-squ.:·················0.01845
208	Time:························13:13:47···Log-Likelihood:················-43384.	212	Time:························13:13:47···Log-Likelihood:················-43384.
Offset 219, 18 lines modified		Offset 223, 14 lines modified
219	disea··········0.0382······0.001·····26.080······0.000·······0.035·······0.041	223	disea··········0.0382······0.001·····26.080······0.000·······0.035·······0.041
220	hlthg·········-0.0441······0.020·····-2.201······0.028······-0.083······-0.005	224	hlthg·········-0.0441······0.020·····-2.201······0.028······-0.083······-0.005
221	hlthf··········0.0173······0.036······0.478······0.632······-0.054·······0.088	225	hlthf··········0.0173······0.036······0.478······0.632······-0.054·······0.088
222	hlthp··········0.1782······0.074······2.399······0.016·······0.033·······0.324	226	hlthp··········0.1782······0.074······2.399······0.016·······0.033·······0.324
223	const··········0.6635······0.025·····26.786······0.000·······0.615·······0.712	227	const··········0.6635······0.025·····26.786······0.000·······0.615·······0.712
224	alpha··········1.2930······0.019·····69.477······0.000·······1.256·······1.329	228	alpha··········1.2930······0.019·····69.477······0.000·······1.256·······1.329
225	==============================================================================	229	==============================================================================
226	/usr/lib/python3/dist-packages/statsmodels/base/model.py:607:
227	ConvergenceWarning:·Maximum·Likelihood·optimization·failed·to·converge.·Check
228	mle_retvals
229	··warnings.warn("Maximum·Likelihood·optimization·failed·to·"
230	\x8\x8\x8\x8\x8·A\x8Al\x8lt\x8te\x8er\x8rn\x8na\x8at\x8ti\x8iv\x8ve\x8e·s\x8so\x8ol\x8lv\x8ve\x8er\x8rs\x8s_\x8?\x8¶·\x8\x8\x8\x8\x8	230	\x8\x8\x8\x8\x8·A\x8Al\x8lt\x8te\x8er\x8rn\x8na\x8at\x8ti\x8iv\x8ve\x8e·s\x8so\x8ol\x8lv\x8ve\x8er\x8rs\x8s_\x8?\x8¶·\x8\x8\x8\x8\x8
231	The·default·method·for·fitting·discrete·data·MLE·models·is·Newton-Raphson.·You	231	The·default·method·for·fitting·discrete·data·MLE·models·is·Newton-Raphson.·You
232	can·use·other·solvers·by·using·the·method·argument:	232	can·use·other·solvers·by·using·the·method·argument:
233	[15]:	233	[15]:
234	mlogit_res·=·mlogit_mod.fit(method="bfgs",·maxiter=250)	234	mlogit_res·=·mlogit_mod.fit(method="bfgs",·maxiter=250)
235	print(mlogit_res.summary())	235	print(mlogit_res.summary())
236	Optimization·terminated·successfully.	236	Optimization·terminated·successfully.


Offset 5, 32 lines modified		Offset 5, 32 lines modified
5	····*·_\x8p_\x8r_\x8e_\x8v_\x8i_\x8o_\x8u_\x8s·\|	5	····*·_\x8p_\x8r_\x8e_\x8v_\x8i_\x8o_\x8u_\x8s·\|
6	····*·_\x8s_\x8t_\x8a_\x8t_\x8s_\x8m_\x8o_\x8d_\x8e_\x8l_\x8s_\x8·_\x80_\x8._\x81_\x84_\x8._\x85_\x8+_\x8d_\x8f_\x8s_\x8g·»	6	····*·_\x8s_\x8t_\x8a_\x8t_\x8s_\x8m_\x8o_\x8d_\x8e_\x8l_\x8s_\x8·_\x80_\x8._\x81_\x84_\x8._\x85_\x8+_\x8d_\x8f_\x8s_\x8g·»
7	····*·_\x8E_\x8x_\x8a_\x8m_\x8p_\x8l_\x8e_\x8s·»	7	····*·_\x8E_\x8x_\x8a_\x8m_\x8p_\x8l_\x8e_\x8s·»
8	····*·Variance·Component·Analysis	8	····*·Variance·Component·Analysis
9	\x8\x8\x8\x8\x8\x8·V\x8Va\x8ar\x8ri\x8ia\x8an\x8nc\x8ce\x8e·C\x8Co\x8om\x8mp\x8po\x8on\x8ne\x8en\x8nt\x8t·A\x8An\x8na\x8al\x8ly\x8ys\x8si\x8is\x8s_\x8?\x8¶·\x8\x8\x8\x8\x8\x8	9	\x8\x8\x8\x8\x8\x8·V\x8Va\x8ar\x8ri\x8ia\x8an\x8nc\x8ce\x8e·C\x8Co\x8om\x8mp\x8po\x8on\x8ne\x8en\x8nt\x8t·A\x8An\x8na\x8al\x8ly\x8ys\x8si\x8is\x8s_\x8?\x8¶·\x8\x8\x8\x8\x8\x8
10	This·notebook·illustrates·variance·components·analysis·for·two-level·nested·and	10	This·notebook·illustrates·variance·components·analysis·for·two-level·nested·and
11	crossed·designs.	11	crossed·designs.
12	[1]:	12	[·]:
13	import·numpy·as·np	13	import·numpy·as·np
14	import·statsmodels.api·as·sm	14	import·statsmodels.api·as·sm
15	from·statsmodels.regression.mixed_linear_model·import·VCSpec	15	from·statsmodels.regression.mixed_linear_model·import·VCSpec
16	import·pandas·as·pd	16	import·pandas·as·pd
17	Make·the·notebook·reproducible	17	Make·the·notebook·reproducible
18	[2]:	18	[·]:
19	np.random.seed(3123)	19	np.random.seed(3123)
20	\x8\x8\x8\x8\x8·N\x8Ne\x8es\x8st\x8te\x8ed\x8d·a\x8an\x8na\x8al\x8ly\x8ys\x8si\x8is\x8s_\x8?\x8¶·\x8\x8\x8\x8\x8	20	\x8\x8\x8\x8\x8·N\x8Ne\x8es\x8st\x8te\x8ed\x8d·a\x8an\x8na\x8al\x8ly\x8ys\x8si\x8is\x8s_\x8?\x8¶·\x8\x8\x8\x8\x8
21	In·our·discussion·below,·“Group·2”·is·nested·within·“Group·1”.·As·a·concrete	21	In·our·discussion·below,·“Group·2”·is·nested·within·“Group·1”.·As·a·concrete
22	example,·“Group·1”·might·be·school·districts,·with·“Group·2”·being·individual	22	example,·“Group·1”·might·be·school·districts,·with·“Group·2”·being·individual
23	schools.·The·function·below·generates·data·from·such·a·population.·In·a·nested	23	schools.·The·function·below·generates·data·from·such·a·population.·In·a·nested
24	analysis,·the·group·2·labels·that·are·nested·within·different·group·1·labels	24	analysis,·the·group·2·labels·that·are·nested·within·different·group·1·labels
25	are·treated·as·independent·groups,·even·if·they·have·the·same·label.·For	25	are·treated·as·independent·groups,·even·if·they·have·the·same·label.·For
26	example,·two·schools·labeled·“school·1”·that·are·in·two·different·school	26	example,·two·schools·labeled·“school·1”·that·are·in·two·different·school
27	districts·are·treated·as·independent·schools,·even·though·they·have·the·same	27	districts·are·treated·as·independent·schools,·even·though·they·have·the·same
28	label.	28	label.
29	[3]:	29	[·]:
30	def·generate_nested(	30	def·generate_nested(
31	····n_group1=200,·n_group2=20,·n_rep=10,·group1_sd=2,·group2_sd=3,	31	····n_group1=200,·n_group2=20,·n_rep=10,·group1_sd=2,·group2_sd=3,
32	unexplained_sd=4	32	unexplained_sd=4
33	):	33	):

34	····#·Group·1·indicators	34	····#·Group·1·indicators
35	····group1·=·np.kron(np.arange(n_group1),·np.ones(n_group2·*·n_rep))	35	····group1·=·np.kron(np.arange(n_group1),·np.ones(n_group2·*·n_rep))
Offset 50, 103 lines modified		Offset 50, 66 lines modified
50	····e·=·unexplained_sd··np.random.normal(size=n_group1··n_group2·*·n_rep)	50	····e·=·unexplained_sd··np.random.normal(size=n_group1··n_group2·*·n_rep)
51	····y·=·effects1·+·effects2·+·e	51	····y·=·effects1·+·effects2·+·e

52	····df·=·pd.DataFrame({"y":·y,·"group1":·group1,·"group2":·group2})	52	····df·=·pd.DataFrame({"y":·y,·"group1":·group1,·"group2":·group2})

53	····return·df	53	····return·df
54	Generate·a·data·set·to·analyze.	54	Generate·a·data·set·to·analyze.
55	[4]:	55	[·]:
56	df·=·generate_nested()	56	df·=·generate_nested()
57	Using·all·the·default·arguments·for·generate_nested,·the·population·values·of	57	Using·all·the·default·arguments·for·generate_nested,·the·population·values·of
58	“group·1·Var”·and·“group·2·Var”·are·2^2=4·and·3^2=9,·respectively.·The	58	“group·1·Var”·and·“group·2·Var”·are·2^2=4·and·3^2=9,·respectively.·The
59	unexplained·variance,·listed·as·“scale”·at·the·top·of·the·summary·table,·has	59	unexplained·variance,·listed·as·“scale”·at·the·top·of·the·summary·table,·has
60	population·value·4^2=16.	60	population·value·4^2=16.
61	[5]:	61	[·]:
62	model1·=·sm.MixedLM.from_formula(	62	model1·=·sm.MixedLM.from_formula(
63	····"y·~·1",	63	····"y·~·1",
64	····re_formula="1",	64	····re_formula="1",
65	····vc_formula={"group2":·"0·+·C(group2)"},	65	····vc_formula={"group2":·"0·+·C(group2)"},
66	····groups="group1",	66	····groups="group1",
67	····data=df,	67	····data=df,
68	)	68	)
69	result1·=·model1.fit()	69	result1·=·model1.fit()
70	print(result1.summary())	70	print(result1.summary())
71	··········Mixed·Linear·Model·Regression·Results
72	==========================================================
73	Model:············MixedLM·Dependent·Variable:·y
74	No.·Observations:·40000···Method:·············REML
75	No.·Groups:·······200·····Scale:··············15.8825
76	Min.·group·size:··200·····Log-Likelihood:·····-116022.3805
77	Max.·group·size:··200·····Converged:··········Yes
78	Mean·group·size:··200.0
79	-----------------------------------------------------------
80	············Coef.···Std.Err.····z·····P>\|z\|··[0.025··0.975]
81	-----------------------------------------------------------
82	Intercept···-0.035·····0.149··-0.232··0.817··-0.326···0.257
83	group1·Var···3.917·····0.112
84	group2·Var···8.742·····0.063
85	==========================================================
86	If·we·wish·to·avoid·the·formula·interface,·we·can·fit·the·same·model·by	71	If·we·wish·to·avoid·the·formula·interface,·we·can·fit·the·same·model·by
87	building·the·design·matrices·manually.	72	building·the·design·matrices·manually.
88	[6]:	73	[·]:
89	def·f(x):	74	def·f(x):
90	····n·=·x.shape[0]	75	····n·=·x.shape[0]
91	····g2·=·x.group2	76	····g2·=·x.group2
92	····u·=·g2.unique()	77	····u·=·g2.unique()
93	····u.sort()	78	····u.sort()
94	····uv·=·{v:·k·for·k,·v·in·enumerate(u)}	79	····uv·=·{v:·k·for·k,·v·in·enumerate(u)}
95	····mat·=·np.zeros((n,·len(u)))	80	····mat·=·np.zeros((n,·len(u)))
96	····for·i·in·range(n):	81	····for·i·in·range(n):
97	········mat[i,·uv[g2.iloc[i]]]·=·1	82	········mat[i,·uv[g2.iloc[i]]]·=·1
98	····colnames·=·["%d"·%·z·for·z·in·u]	83	····colnames·=·["%d"·%·z·for·z·in·u]
99	····return·mat,·colnames	84	····return·mat,·colnames
100	Then·we·set·up·the·variance·components·using·the·VCSpec·class.	85	Then·we·set·up·the·variance·components·using·the·VCSpec·class.
101	[7]:	86	[·]:
102	vcm·=·df.groupby("group1").apply(f).to_list()	87	vcm·=·df.groupby("group1").apply(f).to_list()
103	mats·=·[x[0]·for·x·in·vcm]	88	mats·=·[x[0]·for·x·in·vcm]
104	colnames·=·[x[1]·for·x·in·vcm]	89	colnames·=·[x[1]·for·x·in·vcm]
105	names·=·["group2"]	90	names·=·["group2"]
106	vcs·=·VCSpec(names,·[colnames],·[mats])	91	vcs·=·VCSpec(names,·[colnames],·[mats])
107	/tmp/ipykernel_nnnnnnn/1119967950.py:1:·DeprecationWarning:
108	DataFrameGroupBy.apply·operated·on·the·grouping·columns.·This·behavior·is
109	deprecated,·and·in·a·future·version·of·pandas·the·grouping·columns·will·be
110	excluded·from·the·operation.·Either·pass·`include_groups=False`·to·exclude·the
111	groupings·or·explicitly·select·the·grouping·columns·after·groupby·to·silence
112	this·warning.
113	··vcm·=·df.groupby("group1").apply(f).to_list()
114	Finally·we·fit·the·model.·It·can·be·seen·that·the·results·of·the·two·fits·are	92	Finally·we·fit·the·model.·It·can·be·seen·that·the·results·of·the·two·fits·are
115	identical.	93	identical.
116	[8]:	94	[·]:
117	oo·=·np.ones(df.shape[0])	95	oo·=·np.ones(df.shape[0])
118	model2·=·sm.MixedLM(df.y,·oo,·exog_re=oo,·groups=df.group1,·exog_vc=vcs)	96	model2·=·sm.MixedLM(df.y,·oo,·exog_re=oo,·groups=df.group1,·exog_vc=vcs)
119	result2·=·model2.fit()	97	result2·=·model2.fit()
120	print(result2.summary())	98	print(result2.summary())
121	··········Mixed·Linear·Model·Regression·Results
122	==========================================================
123	Model:············MixedLM·Dependent·Variable:·y
124	No.·Observations:·40000···Method:·············REML
125	No.·Groups:·······200·····Scale:··············15.8825
126	Min.·group·size:··200·····Log-Likelihood:·····-116022.3805
127	Max.·group·size:··200·····Converged:··········Yes
128	Mean·group·size:··200.0
129	-----------------------------------------------------------
130	············Coef.···Std.Err.····z·····P>\|z\|··[0.025··0.975]
131	-----------------------------------------------------------
132	const·······-0.035·····0.149··-0.232··0.817··-0.326···0.257
133	x_re1·Var····3.917·····0.112
134	group2·Var···8.742·····0.063
135	==========================================================
136	\x8\x8\x8\x8\x8·C\x8Cr\x8ro\x8os\x8ss\x8se\x8ed\x8d·a\x8an\x8na\x8al\x8ly\x8ys\x8si\x8is\x8s_\x8?\x8¶·\x8\x8\x8\x8\x8	99	\x8\x8\x8\x8\x8·C\x8Cr\x8ro\x8os\x8ss\x8se\x8ed\x8d·a\x8an\x8na\x8al\x8ly\x8ys\x8si\x8is\x8s_\x8?\x8¶·\x8\x8\x8\x8\x8
137	In·a·crossed·analysis,·the·levels·of·one·group·can·occur·in·any·combination	100	In·a·crossed·analysis,·the·levels·of·one·group·can·occur·in·any·combination
138	with·the·levels·of·the·another·group.·The·groups·in·Statsmodels·MixedLM·are	101	with·the·levels·of·the·another·group.·The·groups·in·Statsmodels·MixedLM·are
139	always·nested,·but·it·is·possible·to·fit·a·crossed·model·by·having·only·one	102	always·nested,·but·it·is·possible·to·fit·a·crossed·model·by·having·only·one
140	group,·and·specifying·all·random·effects·as·variance·components.·Many,·but·not	103	group,·and·specifying·all·random·effects·as·variance·components.·Many,·but·not
141	all·crossed·models·can·be·fit·in·this·way.·The·function·below·generates·a	104	all·crossed·models·can·be·fit·in·this·way.·The·function·below·generates·a
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51580	········"5":·"py:property",	51580	········"5":·"py:property",
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51582	········"7":·"py:exception"	51582	········"7":·"py:exception"
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51591	········"000000":·[197,·198,·202,·207,·209,·219,·234,·254,·257,·258,·4692,·6466],	51591	········"000000":·[197,·198,·202,·207,·209,·219,·234,·254,·257,·258,·4692,·6466],
51592	········"0000000000000002":·[3261,·3286,·3311,·3336,·3367,·3392,·3423,·3448],	51592	········"0000000000000002":·[3261,·3286,·3311,·3336,·3367,·3392,·3423,·3448],
51593	········"00000000e":·219,	51593	········"00000000e":·219,
51594	········"00000015":·2075,	51594	········"00000015":·2075,
Offset 51933, 15 lines modified		Offset 51933, 15 lines modified
51933	········"0099":·[198,·207],	51933	········"0099":·[198,·207],
51934	········"009925":·207,	51934	········"009925":·207,
51935	········"00994468":·226,	51935	········"00994468":·226,
51936	········"009958":·218,	51936	········"009958":·218,
51937	········"009996":·243,	51937	········"009996":·243,
51938	········"009999999999999981":·255,	51938	········"009999999999999981":·255,
51939	········"009d91":·225,	51939	········"009d91":·225,
51940	········"01":·[26,·~~34,·183,·188,·~~190,·196,·197,·201,·202,·203,·206,·210,·214,·216,·217,·219,·220,·221,·229,·230,·233,·234,·236,·239,·240,·241,·243,·244,·245,·246,·247,·248,·249,·250,·251,·252,·253,·254,·255,·257,·258,·260,·261,·265,·267,·268,·371,·388,·446,·504,·563,·619,·67[·...·truncated·by·diffoscope;·len:·247,·SHA:·631812a25~~7dadfc9~~6c8e7~~4b44~~03e65167f~~1563a6~~fe~~437da07660b~~5e~~81bffc56b~~·...·]],	51940	········"01":·[26,·190,·196,·197,·201,·202,·203,·206,·210,·214,·216,·217,·219,·220,·221,·229,·230,·233,·234,·236,·239,·240,·241,·243,·244,·245,·246,·247,·248,·249,·250,·251,·252,·253,·254,·255,·257,·258,·260,·261,·265,·267,·268,·371,·388,·446,·504,·563,·619,·674,·727,·791,·8[·...·truncated·by·diffoscope;·len:·203,·SHA:·119f28ebcceb61866733730d8ea9b1402f7ebe6cf3e029bb54caa6537c791d2a·...·]],
51941	········"010":·[198,·201,·207,·208,·217,·259,·267,·3935],	51941	········"010":·[198,·201,·207,·208,·217,·259,·267,·3935],
51942	········"010034":·226,	51942	········"010034":·226,
51943	········"010052":·196,	51943	········"010052":·196,
51944	········"01006072":·222,	51944	········"01006072":·222,
51945	········"0102":·208,	51945	········"0102":·208,
51946	········"010200":·218,	51946	········"010200":·218,
51947	········"010212":·[86,·117,·288,·360,·435,·493,·551,·608,·663,·716,·778,·842,·920,·1000,·1085,·1140,·1214,·1254,·1448,·1582,·2012,·2142,·2182,·2410,·2608,·2741,·2805,·2882,·2932,·3003,·3116,·3244,·3520,·3584,·3639,·4334,·4413,·4499,·4616,·4792,·5061,·5169,·5269,·5579,·5747,·5966,·6075],	51947	········"010212":·[86,·117,·288,·360,·435,·493,·551,·608,·663,·716,·778,·842,·920,·1000,·1085,·1140,·1214,·1254,·1448,·1582,·2012,·2142,·2182,·2410,·2608,·2741,·2805,·2882,·2932,·3003,·3116,·3244,·3520,·3584,·3639,·4334,·4413,·4499,·4616,·4792,·5061,·5169,·5269,·5579,·5747,·5966,·6075],
Offset 52119, 15 lines modified		Offset 52119, 15 lines modified
52119	········"01956437":·226,	52119	········"01956437":·226,
52120	········"01958745":·196,	52120	········"01958745":·196,
52121	········"0196433":·196,	52121	········"0196433":·196,
52122	········"0198":·208,	52122	········"0198":·208,
52123	········"0198821087258905":·[3262,·3287,·3312,·3337,·3368,·3393,·3424,·3449],	52123	········"0198821087258905":·[3262,·3287,·3312,·3337,·3368,·3393,·3424,·3449],
52124	········"01989341":·219,	52124	········"01989341":·219,