def test_model_combo_regi_error(self):
#Columbus:
reg = SP.GM_Combo_Regimes(self.y,
self.X1,
self.regimes,
self.yd,
self.q,
w=self.w,
regime_lag_sep=True,
regime_err_sep=True)
betas = np.array([[42.01035248], [-0.13938772], [-0.6528306],
[0.54737621], [0.2684419], [34.02473255],
[-0.14920259], [-0.48972903], [0.65883658],
[-0.17174845]])
np.testing.assert_array_almost_equal(reg.betas, betas, 4)
vm = np.array([
153.58614432, 2.96302131, -3.26211855, -2.46914703, 0., 0., 0., 0.
])
np.testing.assert_array_almost_equal(reg.vm[0], vm, 4)
u = np.array([7.73968703])
np.testing.assert_array_almost_equal(reg.u[0], u, 4)
predy = np.array([7.98629297])
np.testing.assert_array_almost_equal(reg.predy[0], predy, 4)
e = np.array([6.45052714])
np.testing.assert_array_almost_equal(reg.e_filtered[0], e, 4)
chow_r = np.array([[1.00886404e-01, 7.50768497e-01],
[3.61843271e-05, 9.95200481e-01],
[4.69585772e-02, 8.28442711e-01],
[8.13275259e-02, 7.75506385e-01]])
np.testing.assert_array_almost_equal(reg.chow.regi, chow_r, 4)
chow_j = 0.28479988992843119
self.assertAlmostEqual(reg.chow.joint[0], chow_j)
#Artficial:
model = SP.GM_Combo_Regimes(self.y_a,
self.x_a1,
yend=self.x_a2,
q=self.q_a,
regimes=self.regi_a,
w=self.w_a,
regime_err_sep=True,
regime_lag_sep=True)
model1 = GM_Combo(self.y_a[0:(self.n2)].reshape((self.n2), 1),
self.x_a1[0:(self.n2)],
yend=self.x_a2[0:(self.n2)],
q=self.q_a[0:(self.n2)],
w=self.w_a1)
model2 = GM_Combo(self.y_a[(self.n2):].reshape((self.n2), 1),
self.x_a1[(self.n2):],
yend=self.x_a2[(self.n2):],
q=self.q_a[(self.n2):],
w=self.w_a1)
tbetas = np.vstack((model1.betas, model2.betas))
np.testing.assert_array_almost_equal(model.betas, tbetas)
vm = np.hstack((model1.vm.diagonal(), model2.vm.diagonal()))
def test_model_combo(self):
reg = SP.GM_Combo_Regimes(self.y,
self.X1,
self.regimes,
self.yd,
self.q,
w=self.w)
predy_e = np.array([18.82774339])
np.testing.assert_array_almost_equal(reg.predy_e[0], predy_e, 4)
betas = np.array([[36.44798052], [-0.7974482], [30.53782661],
[-0.72602806], [-0.30953121], [-0.21736652],
[0.64801059], [-0.16601265]])
np.testing.assert_array_almost_equal(reg.betas, betas, 4)
u = np.array([0.84393304])
np.testing.assert_array_almost_equal(reg.u[0], u, 4)
e_filtered = np.array([0.4040027])
np.testing.assert_array_almost_equal(reg.e_filtered[0], e_filtered, 4)
predy = np.array([14.88204696])
np.testing.assert_array_almost_equal(reg.predy[0], predy, 4)
n = 49
self.assertAlmostEqual(reg.n, n)
k = 7
self.assertAlmostEqual(reg.k, k)
y = np.array([15.72598])
np.testing.assert_array_almost_equal(reg.y[0], y, 4)
x = np.array([[0., 0., 1., 19.531]])
np.testing.assert_array_almost_equal(reg.x[0].toarray(), x, 4)
yend = np.array([[0., 80.467003, 24.7142675]])
np.testing.assert_array_almost_equal(reg.yend[0].toarray(), yend, 4)
z = np.array([[0., 0., 1., 19.531, 0., 80.467003, 24.7142675]])
np.testing.assert_array_almost_equal(reg.z[0].toarray(), z, 4)
my = 35.128823897959187
self.assertAlmostEqual(reg.mean_y, my)
sy = 16.732092091229699
self.assertAlmostEqual(reg.std_y, sy)
vm = np.array([
109.23549239, -0.19754121, 84.29574673, -1.99317178, -1.60123994,
-0.1252719, -1.3930344
])
np.testing.assert_array_almost_equal(reg.vm[0], vm, 4)
sig2 = 94.98610921110007
self.assertAlmostEqual(reg.sig2, sig2, 4)
pr2 = 0.6493586702255537
self.assertAlmostEqual(reg.pr2, pr2)
pr2_e = 0.5255332447240576
self.assertAlmostEqual(reg.pr2_e, pr2_e)
std_err = np.array([
10.45157846, 0.93942923, 11.38484969, 0.60774708, 0.44461334,
0.15871227, 0.15738141
])
np.testing.assert_array_almost_equal(reg.std_err, std_err, 4)
chow_r = np.array([[0.49716076, 0.48075032], [0.00405377, 0.94923363],
[0.03866684, 0.84411016]])
np.testing.assert_array_almost_equal(reg.chow.regi, chow_r, 4)
chow_j = 0.64531386285872072
self.assertAlmostEqual(reg.chow.joint[0], chow_j)