'Results generated with
data = sm.datasets.spector.load()
data.exog = sm.add_constant(data.exog, prepend=True)
alpha = np.array([0.1, 0.2, 0.3, 10])
res2 = sm.Probit(data.endog, data.exog).fit_regularized(
method="l1", alpha=alpha, disp=0, trim_mode=\'auto\',
auto_trim_tol=0.02, acc=1e-10, maxiter=1000)'

def probit(self):

    nan = np.nan
    self.params = [(-5.40476992), 1.25018458, 0.04744558, 0.0]
    self.conf_int = [[(-9.44077951), (-1.36876033)], [0.03716721, 2.46320194], [(-0.09727571), 0.19216687], [np.nan, np.nan]]
    self.bse = [2.05922641, 0.61889778, 0.07383875, np.nan]
    self.nnz_params = 3
    self.aic = 38.39977387754293
    self.bic = 42.796981585942106
    self.cov_params = [[4.24041339, (-0.83432592), (-0.06827915), nan], [(-0.83432592), 0.38303447, (-0.01700249), nan], [(-0.06827915), (-0.01700249), 0.00545216, nan], [nan, nan, nan, nan]]
