def test_auto_bandwidth(trivariate_data):
y, x = trivariate_data
res = phillips_ouliaris(y, x)
assert isinstance(res.summary(), Summary)
assert int(res.bandwidth) != res.bandwidth
res = phillips_ouliaris(y, x, force_int=True)
assert int(res.bandwidth) == res.bandwidth
def test_p_test_direct(trivariate_data, trend, bandwidth):
y, x = trivariate_data
y = np.asarray(y)
x = np.asarray(x)
z = np.column_stack([y, x])
ref_p_u, ref_p_z = p_tests(z, bandwidth, trend)
p_u = phillips_ouliaris(y, x, trend=trend, bandwidth=bandwidth, test_type="Pu")
p_z = phillips_ouliaris(y, x, trend=trend, bandwidth=bandwidth, test_type="Pz")
assert_allclose(p_u.stat, ref_p_u)
assert_allclose(p_z.stat, ref_p_z)
assert isinstance(p_u.summary(), Summary)
assert isinstance(p_z.summary(), Summary)
def test_z_test_direct(trivariate_data, trend, bandwidth):
y, x = trivariate_data
y = np.asarray(y)
x = np.asarray(x)
z = np.column_stack([y, x])
ref_z_a, ref_z_t = z_tests(z, bandwidth, trend)
z_a = phillips_ouliaris(y, x, trend=trend, bandwidth=bandwidth, test_type="Za")
z_t = phillips_ouliaris(y, x, trend=trend, bandwidth=bandwidth, test_type="Zt")
assert_allclose(z_a.stat, ref_z_a)
assert_allclose(z_t.stat, ref_z_t)
assert isinstance(z_a.summary(), Summary)
assert isinstance(z_t.summary(), Summary)
def test_smoke(trivariate_data, trend, test_type, kernel, bandwidth, force_int):
y, x = trivariate_data
res = phillips_ouliaris(
y,
x,
trend=trend,
test_type=test_type,
kernel=kernel,
bandwidth=bandwidth,
force_int=force_int,
)
assert isinstance(res.stat, float)
def test_errors(trivariate_data):
y, x = trivariate_data
with pytest.raises(ValueError, match="kernel is not a known estimator."):
phillips_ouliaris(y, x, kernel="fancy-kernel")
with pytest.raises(ValueError, match="Unknown test_type: z-alpha."):
phillips_ouliaris(y, x, test_type="z-alpha")