

@classmethod
def setupClass(cls):
    anes_data = sm.datasets.anes96.load()
    anes_exog = anes_data.exog
    anes_exog = sm.add_constant(anes_exog, prepend=False)
    mlogit_mod = sm.MNLogit(anes_data.endog, anes_exog)
    alpha = (10.0 * np.ones(((mlogit_mod.J - 1), mlogit_mod.K)))
    alpha[(- 1), :] = 0
    cls.res1 = mlogit_mod.fit_regularized(method='l1', alpha=alpha, trim_mode='auto', auto_trim_tol=0.02, acc=1e-10, disp=0)
    res2 = DiscreteL1()
    res2.mnlogit()
    cls.res2 = res2

dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/discrete/tests/test_discrete.py TestMNLogitL1.setupClass/original