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_rvs(self): """Test simulation.""" lam = [.5, 1.5, 2] skst = MvSN(ndim=len(lam), lam=lam) size = 10 rvs = skst.rvs(size=size) self.assertEqual(rvs.shape, (size, len(lam)))
def test_param_array(self): """Test pdf.""" ndim, nobs = 1, 10 size = (nobs, ndim) lam = np.ones((nobs, ndim)) * .5 skst = MvSN(ndim=ndim, lam=lam) data = np.random.normal(size=size) pdf = skst.pdf(data) self.assertEqual(pdf.ndim, ndim) self.assertEqual(pdf.shape, (size[0], ))
def test_likelihood(self): """Test log-likelihood.""" lam = [.5, 1.5, 2] theta = np.array(lam) size = (10, len(lam)) data = np.random.normal(size=size) skst = MvSN(ndim=len(lam), 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_cdf(self): """Test cdf.""" lam = 1.5 skst = MvSN(ndim=1, lam=lam) cdf = skst.cdf(np.zeros(1)) self.assertIsInstance(cdf, float) lam = [1.5, .5] skst = MvSN(ndim=len(lam), lam=lam) cdf = skst.cdf(np.zeros(2) - 10) self.assertIsInstance(cdf, float)
def test_init(self): """Test __init__.""" skst = MvSN(ndim=3) self.assertIsInstance(skst.lam, np.ndarray) lam = [.5, 1.5] skst = MvSN(ndim=len(lam), lam=lam) npt.assert_array_equal(skst.lam, np.array(lam)) mu, sigma = [.5, .4], np.ones((2, 2)) skst = MvSN(ndim=len(lam), 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)) lam = [1.5, .5] skst.from_theta(np.array(lam)) npt.assert_array_equal(skst.lam, np.array(lam)) size = len(lam) data = np.random.normal(size=size) skst = MvSN(ndim=len(lam), data=data) npt.assert_array_equal(skst.data, np.atleast_2d(data))
def test_quantile(self): """Test quantile.""" lam = 1.5 skst = MvSN(ndim=1, 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_dimensions(self): """Test dimensions.""" lam = .5 mvsn = MvSN(lam=lam, ndim=1) self.assertEqual(mvsn.ndim, 1)
def test_pdf(self): """Test pdf.""" lam = .5 skst = MvSN(ndim=1, 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], )) lam = [.5, 1.5, 2] skst = MvSN(ndim=len(lam), 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 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()