def mnlogit(self):
        self.params = [[ 0.00100163, -0.05864195, -0.06147822, -0.04769671, -0.05222987,
            -0.09522432],
           [ 0.        ,  0.03186139,  0.12048999,  0.83211915,  0.92330292,
             1.5680646 ],
           [-0.0218185 , -0.01988066, -0.00808564, -0.00487463, -0.01400173,
            -0.00562079],
           [ 0.        ,  0.03306875,  0.        ,  0.02362861,  0.05486435,
             0.14656966],
           [ 0.        ,  0.04448213,  0.03252651,  0.07661761,  0.07265266,
             0.0967758 ],
           [ 0.90993803, -0.50081247, -2.08285102, -5.26132955, -4.86783179,
            -9.31537963]]
        self.conf_int = [[[ -0.0646223 ,   0.06662556],
            [         np.nan,          np.nan],
            [ -0.03405931,  -0.00957768],
            [         np.nan,          np.nan],
            [         np.nan,          np.nan],
            [  0.26697895,   1.55289711]],

           [[ -0.1337913 ,   0.01650741],
            [ -0.14477255,   0.20849532],
            [ -0.03500303,  -0.00475829],
            [ -0.11406121,   0.18019871],
            [  0.00479741,   0.08416684],
            [ -1.84626136,   0.84463642]],

           [[ -0.17237962,   0.04942317],
            [ -0.15146029,   0.39244026],
            [ -0.02947379,   0.01330252],
            [         np.nan,          np.nan],
            [ -0.02501483,   0.09006785],
            [ -3.90379391,  -0.26190812]],

           [[ -0.12938296,   0.03398954],
            [  0.62612955,   1.03810876],
            [ -0.02046322,   0.01071395],
            [ -0.13738534,   0.18464256],
            [  0.03017236,   0.12306286],
            [ -6.91227465,  -3.61038444]],

           [[ -0.12469773,   0.02023799],
            [  0.742564  ,   1.10404183],
            [ -0.02791975,  -0.00008371],
            [ -0.08491561,   0.19464431],
            [  0.0332926 ,   0.11201273],
            [ -6.29331126,  -3.44235233]],

           [[ -0.17165567,  -0.01879296],
            [  1.33994079,   1.79618841],
            [ -0.02027503,   0.00903345],
            [ -0.00267819,   0.29581751],
            [  0.05343135,   0.14012026],
            [-11.10419107,  -7.52656819]]]

        self.bse = [[ 0.03348221,  0.03834221,  0.05658338,  0.04167742,  0.03697408,
                 0.03899631],
               [        np.nan,  0.09012101,  0.13875269,  0.10509867,  0.09221543,
                 0.11639184],
               [ 0.00624543,  0.00771564,  0.01091253,  0.00795351,  0.00710116,
                 0.00747679],
               [        np.nan,  0.07506769,         np.nan,  0.08215148,  0.07131762,
                 0.07614826],
               [        np.nan,  0.02024768,  0.02935837,  0.02369699,  0.02008204,
                 0.02211492],
               [ 0.32804638,  0.68646613,  0.92906957,  0.84233441,  0.72729881,
                 0.91267567]]

        self.nnz_params = 32
        self.aic = 3019.4391360294126
        self.bic = 3174.6431733460686
Results generated with
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/discrete/tests/results/results_discrete.py/DiscreteL1.mnlogit