def test_pdf(self):
"""Test pdf method."""
skewt = SkewStudent()
num = 50
arg = np.linspace(-1, 1, num)
pdf = skewt.pdf(arg)
self.assertEqual(pdf.shape[0], num)
self.assertIsInstance(skewt.pdf(0), float)
def test_pdf(self):
"""Test pdf method."""
skewt = SkewStudent()
num = 50
arg = np.linspace(-1, 1, num)
pdf = skewt.pdf(arg)
self.assertEqual(pdf.shape[0], num)
self.assertIsInstance(skewt.pdf(0), float)
def test_compare_with_t(self):
"""Compare with standard t distribution."""
eta = 5
skewt = SkewStudent(eta=eta, lam=0)
scale = 1/(eta/(eta-2))**.5
standt = t(eta, scale=scale)
arg = np.linspace(-2, 2, 100)
np.testing.assert_array_almost_equal(skewt.pdf(arg), standt.pdf(arg))
np.testing.assert_array_almost_equal(skewt.cdf(arg), standt.cdf(arg))
arg = np.linspace(.01, .99, 100)
np.testing.assert_array_almost_equal(skewt.ppf(arg), standt.ppf(arg))
def test_compare_with_t(self):
"""Compare with standard t distribution."""
eta = 5
skewt = SkewStudent(eta=eta, lam=0)
scale = 1 / (eta / (eta - 2))**.5
standt = t(eta, scale=scale)
arg = np.linspace(-2, 2, 100)
np.testing.assert_array_almost_equal(skewt.pdf(arg), standt.pdf(arg))
np.testing.assert_array_almost_equal(skewt.cdf(arg), standt.cdf(arg))
arg = np.linspace(.01, .99, 100)
np.testing.assert_array_almost_equal(skewt.ppf(arg), standt.ppf(arg))
