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,)))