#NEWLINE# def logit( self ) : #NEWLINE# #INDENT# '\n        Results generated with:\n            data = sm.datasets.spector.load()\n            data.exog = sm.add_constant(data.exog, prepend=True)\n            alpha = 3 * np.array([0, 1, 1, 1])\n            res2 = sm.Logit(data.endog, data.exog).fit_regularized(\n                method="l1", alpha=alpha, disp=0, trim_mode=\'size\',\n                size_trim_tol=1e-5, acc=1e-10, maxiter=1000)\n        ' #NEWLINE# nan = np . nan #NEWLINE# self . params = [ ( - 4.10271595 ) , 0.0 , 0.15493781 , 0.0 ] #NEWLINE# self . conf_int = [ [ ( - 9.15205122 ) , 0.94661932 ] , [ nan , nan ] , [ ( - 0.06539482 ) , 0.37527044 ] , [ nan , nan ] ] #NEWLINE# self . bse = [ 2.5762388 , self , 0.11241668 , nan ] #NEWLINE# self . nnz_params = 2 #NEWLINE# self . aic = 42.09143936858367 #NEWLINE# self . bic = 45.02291117418312 #NEWLINE# self . cov_params = [ [ 6.63700638 , nan , ( - 0.28636261 ) , nan ] , [ nan , nan , nan , nan ] , [ ( - 0.28636261 ) , nan , 0.01263751 , nan ] , [ nan , nan , nan , nan ] ]