def test_regression_2(self):
np.random.seed(42)
data = np.random.randn(100) * 2.0
me = GaussianQuadraticTest(self.grad_log_normal)
U_stat,_ = me.get_statistic_multiple(data)
pval = me.compute_pvalue(U_stat)
assert pval == 0.0
def test_regression_2(self):
np.random.seed(42)
data = np.random.randn(100) * 2.0
me = GaussianQuadraticTest(self.grad_log_normal)
U_stat, _ = me.get_statistic_multiple(data)
pval = me.compute_pvalue(U_stat)
assert pval == 0.0
def test_two_dimensional_tests_alt(self):
np.random.seed(43)
me = GaussianQuadraticTest(self.grad_log_normal)
samples = np.random.randn(100,2)+1
U,_ = me.get_statisitc_two_dim(100,samples,1)
p = me.compute_pvalue(U)
assert p == 0
def test_two_dimensional_tests_alt(self):
np.random.seed(43)
me = GaussianQuadraticTest(self.grad_log_normal)
samples = np.random.randn(100, 2) + 1
U, _ = me.get_statisitc_two_dim(100, samples, 1)
p = me.compute_pvalue(U)
assert p == 0
