def test_normal(self):
dist = Normal()
ll1 = dist.loglikelihood([], self.resids, self.sigma2)
scipy_dist = stats.norm
ll2 = scipy_dist.logpdf(self.resids, scale=np.sqrt(self.sigma2)).sum()
assert_almost_equal(ll1, ll2)
assert_equal(dist.num_params, 0)
bounds = dist.bounds(self.resids)
assert_equal(len(bounds), 0)
a, b = dist.constraints()
assert_equal(len(a), 0)
assert_array_equal(dist.starting_values(self.resids), np.empty((0, )))
def test_normal(self):
dist = Normal()
ll1 = dist.loglikelihoood([], self.resids, self.sigma2)
scipy_dist = stats.norm
ll2 = scipy_dist.logpdf(self.resids, scale=np.sqrt(self.sigma2)).sum()
assert_almost_equal(ll1, ll2)
assert_equal(dist.num_params, 0)
bounds = dist.bounds(self.resids)
assert_equal(len(bounds), 0)
a, b = dist.constraints()
assert_equal(len(a), 0)
assert_array_equal(dist.starting_values(self.resids), np.empty((0,)))
