def test_rvs(self): """Test simulation.""" eta, lam = 100, [.5, 1.5, 2] skst = SkStDM(ndim=len(lam), eta=eta, lam=lam) size = 10 rvs = skst.rvs(size=size) self.assertEqual(rvs.shape, (size, len(lam)))
def compute_copula_likelihood(): eta, lam = 100, 1.5 skst_univ = SkStDM(ndim=1, eta=eta, lam=lam) eta, lam = 100, [1.5, -2] skst_mult = SkStDM(ndim=len(lam), eta=eta, lam=lam) data = np.random.normal(size=(10, 2)) ll = likelihood(skst_univ, skst_mult, data) print(ll)
def test_likelihood(self): """Test log-likelihood.""" eta, lam = 100, [.5, 1.5, 2] theta = np.concatenate((np.atleast_1d(eta), lam)) size = (10, len(lam)) data = np.random.normal(size=size) skst = SkStDM(ndim=len(lam), eta=eta, lam=lam, data=data) logl1 = skst.likelihood(theta) logl2 = skst.likelihood(theta * 2) self.assertIsInstance(logl1, float) self.assertNotEqual(logl1, logl2) npt.assert_array_equal(skst.data, data)
def test_init(self): """Test __init__.""" skst = SkStDM(ndim=3) self.assertIsInstance(skst.eta, np.ndarray) self.assertIsInstance(skst.lam, np.ndarray) eta, lam = 10, [.5, 1.5] skst = SkStDM(ndim=len(lam), eta=eta, lam=lam) npt.assert_array_equal(skst.eta, np.array(eta)) npt.assert_array_equal(skst.lam, np.array(lam)) mu, sigma = [.5, .4], np.ones((2, 2)) skst = SkStDM(ndim=len(lam), eta=eta, lam=lam, mu=mu, sigma=sigma) npt.assert_array_equal(skst.mu, np.array(mu)) npt.assert_array_equal(skst.sigma, np.array(sigma)) npt.assert_array_equal(skst.const_mu(), np.array(mu)) npt.assert_array_equal(skst.const_sigma(), np.array(sigma)) eta, lam = 15, [1.5, .5] skst.from_theta(np.concatenate((np.atleast_1d(eta), lam))) npt.assert_array_equal(skst.eta, np.array(eta)) npt.assert_array_equal(skst.lam, np.array(lam)) size = (10, len(lam)) data = np.random.normal(size=size) skst = SkStDM(ndim=len(lam), data=data) npt.assert_array_equal(skst.data, data)
def test_cdf(self): """Test cdf.""" eta, lam = 20, 1.5 skst = SkStDM(ndim=1, eta=eta, lam=lam) cdf = skst.cdf(np.zeros(1)) self.assertIsInstance(cdf, float) eta, lam = 20, [1.5, .5] skst = SkStDM(ndim=len(lam), eta=eta, lam=lam) cdf = skst.cdf(np.zeros(2) - 10) self.assertIsInstance(cdf, float)
def plot_bidensity(): lam = [1.5, -2] mvsn = MvSN(ndim=len(lam), lam=lam) mvsn.plot_bidensity() eta = 20 skst = MvSt(ndim=2, eta=eta) skst.plot_bidensity() eta, lam = [20, 5], [1.5, .5] skst = SkStJR(ndim=len(lam), eta=eta, lam=lam) skst.plot_bidensity() eta, lam = 20, [1.5, .5] skst = SkStBL(ndim=len(lam), eta=eta, lam=lam) skst.plot_bidensity() eta, lam = 20, [1.5, -2] skst = SkStDM(ndim=len(lam), eta=eta, lam=lam) skst.plot_bidensity() eta, lam = 20, [1.5, -2] skst = SkStAC(ndim=len(lam), eta=eta, lam=lam) skst.plot_bidensity()
def test_quantile(self): """Test quantile.""" eta, lam = 20, 1.5 skst = SkStDM(ndim=1, eta=eta, lam=lam) arg = -2. cdf = skst.cdf(arg) ppf = skst.ppf(cdf) self.assertAlmostEqual(ppf, arg) arg = -.1 * np.ones(3) cdf = skst.cdf_vec(arg) quantiles = skst.ppf_vec(cdf) npt.assert_array_almost_equal(arg, quantiles)
def test_pdf(self): """Test pdf.""" eta, lam = 30, .5 skst = SkStDM(ndim=1, eta=eta, lam=lam) size = (10, 1) data = np.random.normal(size=size) pdf = skst.pdf(data) self.assertEqual(pdf.ndim, 1) self.assertEqual(pdf.shape, (size[0], )) eta, lam = 30, [.5, 1.5, 2] skst = SkStDM(ndim=len(lam), eta=eta, lam=lam) size = (10, len(lam)) data = np.random.normal(size=size) pdf = skst.pdf(data) self.assertEqual(pdf.ndim, 1) self.assertEqual(pdf.shape, (size[0], ))
def compute_univ_cdf(): eta, lam = 20, 1.5 skst = SkStJR(ndim=1, eta=eta, lam=lam) print(skst.cdf(np.zeros(1))) eta, lam = 20, 1.5 skst = SkStBL(ndim=1, eta=eta, lam=lam) print(skst.cdf(np.zeros(1))) eta, lam = 100, 1.5 skst = SkStDM(ndim=1, eta=eta, lam=lam) print(skst.cdf(np.zeros(1) + 10))
def compute_cdf(): eta, lam = [20, 5], [1.5, .5] skst = SkStJR(ndim=len(lam), eta=eta, lam=lam) print(skst.cdf(np.zeros(2))) eta, lam = 20, [1.5, .5] skst = SkStBL(ndim=len(lam), eta=eta, lam=lam) print(skst.cdf(np.zeros(2))) eta, lam = 100, [1.5, -2] skst = SkStDM(ndim=len(lam), eta=eta, lam=lam) print(skst.cdf(np.zeros(2)))
def compute_quantile(): eta, lam = 20, 1.5 skst = SkStJR(ndim=1, eta=eta, lam=lam) cdf = skst.cdf(np.zeros(1) - 2) print(skst.ppf(cdf)) eta, lam = 20, 1.5 skst = SkStBL(ndim=1, eta=eta, lam=lam) cdf = skst.cdf(np.zeros(1) - 2) print(skst.ppf(cdf)) eta, lam = 100, 1.5 skst = SkStDM(ndim=1, eta=eta, lam=lam) cdf = skst.cdf(np.zeros(1) - 2) print(skst.ppf(cdf))
def plot_bidensity_simulated(): size = int(1e4) lam = [1.5, -2] mvsn = MvSN(ndim=len(lam), lam=lam) mvsn.plot_bidensity() rvs = mvsn.rvs(size=size) sns.kdeplot(rvs, shade=True) plt.axis('square') plt.xlim([-2, 2]) plt.ylim([-2, 2]) plt.show() eta = 20 skst = MvSt(ndim=2, eta=eta) skst.plot_bidensity() rvs = skst.rvs(size=size) sns.kdeplot(rvs, shade=True) plt.axis('square') plt.xlim([-2, 2]) plt.ylim([-2, 2]) plt.show() eta, lam = [20, 5], [1.5, .5] skst = SkStJR(ndim=len(lam), eta=eta, lam=lam) skst.plot_bidensity() rvs = skst.rvs(size=size) sns.kdeplot(rvs, shade=True) plt.axis('square') plt.xlim([-2, 2]) plt.ylim([-2, 2]) plt.show() eta, lam = 20, [1.5, .5] skst = SkStBL(ndim=len(lam), eta=eta, lam=lam) skst.plot_bidensity() rvs = skst.rvs(size=size) sns.kdeplot(rvs, shade=True) plt.axis('square') plt.xlim([-2, 2]) plt.ylim([-2, 2]) plt.show() eta, lam = 20, [1.5, -2] skst = SkStDM(ndim=len(lam), eta=eta, lam=lam) skst.plot_bidensity() rvs = skst.rvs(size=size) sns.kdeplot(rvs, shade=True) plt.axis('square') plt.xlim([-2, 2]) plt.ylim([-2, 2]) plt.show() eta, lam = 20, [1.5, -2] skst = SkStAC(ndim=len(lam), eta=eta, lam=lam) skst.plot_bidensity() rvs = skst.rvs(size=size) sns.kdeplot(rvs, shade=True) plt.axis('square') plt.xlim([-2, 2]) plt.ylim([-2, 2]) plt.show()