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alkaline-ml / statsmodels   python

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Version: 0.11.1 

/ regression / tests / results / results_theil_textile.py

import numpy as np

from statsmodels.tools.testing import ParamsTableTestBunch

est = dict(
    rmse=.0136097497582343,
    r2=.9741055881598619,
    N=17,
    df_r=14,
    compat=.860625753607033,
    vrank=2,
    pvalue=.6503055973535645,
    frac_sample=.7935370014985163,
    frac_prior=.2064629985014838,
    cmd="tgmixed",
    predict="regres_p",
    depvar="lconsump",
    marginsok="XB default",
    cmdline="tgmixed lconsump lincome lprice, prior(lprice -0.7 0.15 lincome 1 0.15) cov(lprice lincome -0.01)",  # noqa:E501
    prior="lprice -0.7 0.15 lincome 1 0.15",
    properties="b V",
)

params_table = np.array([
    1.0893571039001,  .10338923727975,   10.53646523141,  4.871483239e-08,
    .86760924410848,  1.3111049636916,               14,  2.1447866879178,
    0, -.82054628653043,  .03496499383295, -23.467651401591,
    1.218701708e-12, -.89553873984647, -.74555383321439,               14,
    2.1447866879178,                0,  1.4666439879147,  .20347802665937,
    7.2078740490733,  4.509300573e-06,  1.0302270250519,  1.9030609507775,
    14,  2.1447866879178,                0]).reshape(3, 9)

params_table_colnames = 'b se t pvalue ll ul df crit eform'.split()

params_table_rownames = 'lincome lprice _cons'.split()

cov = np.array([
    .01068933438529, -.00081953185523,  -.0199747086722, -.00081953185523,
    .00122255079374, -.00064024357954,  -.0199747086722, -.00064024357954,
    .04140330733319]).reshape(3, 3)

cov_colnames = 'lincome lprice _cons'.split()

cov_rownames = 'lincome lprice _cons'.split()

cov_prior = np.array([
    .0225,             -.01,                0,             -.01,
    .0225,                0,                0,                0,
    0]).reshape(3, 3)

cov_prior_colnames = 'lincome lprice _cons'.split()

cov_prior_rownames = 'lincome lprice _cons'.split()


results_theil_textile = ParamsTableTestBunch(
    params_table=params_table,
    params_table_colnames=params_table_colnames,
    params_table_rownames=params_table_rownames,
    cov=cov,
    cov_colnames=cov_colnames,
    cov_rownames=cov_rownames,
    cov_prior=cov_prior,
    cov_prior_colnames=cov_prior_colnames,
    cov_prior_rownames=cov_prior_rownames,
    **est
)