'Results generated with
params = np.zeros((3, 4))
alphas = np.array(
[[0.1, 0.1, 0.1, 0.1],
[0.4, 0.4, 0.5, 0.5], [0.5, 0.5, 1, 1]])
model = sm.Logit(data.endog, data.exog)
for i in range(3):
alpha = alphas[i, :]
res2 = model.fit_regularized(method="l1", alpha=alpha, disp=0, acc=1e-10,
maxiter=1000, trim_mode=\'off\')
params[i, :] = res2.params
print params'

def sweep(self):

    self.params = [[(-10.37593611), 2.27080968, 0.06670638, 2.05723691], [(-5.32670811), 1.18216019, 0.01402395, 1.45178712], [(-3.92630318), 0.90126958, (-0.0), 1.09498178]]
