def test_model2(self):
reg = ML_Lag_Regimes(self.y,self.x,self.regimes,w=self.w,name_y=self.y_name,name_x=self.x_names,\
name_w=self.w_name,name_ds=self.ds_name,name_regimes="CITCOU", regime_lag_sep=True)
betas = np.array([[-0.71589799], [4.40910538], [-0.08652467],
[0.46266265], [0.1627765], [-5.00594358],
[2.91060349], [-0.18207394], [0.71129227],
[0.66753263]])
np.testing.assert_allclose(reg.betas, betas, RTOL)
vm = np.array([
55.3593679, -7.22927797, -0.19487326, 0.6030953, -0.52249569, 0.,
0., 0., 0., 0.
])
np.testing.assert_allclose(reg.vm[0], vm, RTOL)
u = np.array([34.03630518])
np.testing.assert_allclose(reg.u[0], u, RTOL)
predy = np.array([12.96369482])
np.testing.assert_allclose(reg.predy[0], predy, RTOL)
e = np.array([32.46466912])
np.testing.assert_allclose(reg.e_pred[0], e, RTOL)
chow_r = np.array([[0.15654726, 0.69235548], [0.43533847, 0.509381],
[0.60552514, 0.43647766], [0.59214981, 0.441589],
[11.69437282, 0.00062689]])
np.testing.assert_allclose(reg.chow.regi, chow_r, RTOL)
chow_j = 21.978012275873063
np.testing.assert_allclose(reg.chow.joint[0], chow_j, RTOL)
def test_model1(self):
reg = ML_Lag_Regimes(self.y,self.x,self.regimes,w=self.w,name_y=self.y_name,name_x=self.x_names,\
name_w=self.w_name,name_ds=self.ds_name,name_regimes="CITCOU", regime_lag_sep=False)
betas = np.array([[-15.00586577],
[ 4.49600801],
[ -0.03180518],
[ 0.34995882],
[ -4.54040395],
[ 3.92187578],
[ -0.17021393],
[ 0.81941371],
[ 0.53850323]])
np.testing.assert_array_almost_equal(reg.betas,betas,4)
u = np.array([ 32.73718478])
np.testing.assert_array_almost_equal(reg.u[0],u,4)
predy = np.array([ 14.26281522])
np.testing.assert_array_almost_equal(reg.predy[0],predy,4)
n = 211
self.assertAlmostEqual(reg.n,n,4)
k = 9
self.assertAlmostEqual(reg.k,k,4)
y = np.array([ 47.])
np.testing.assert_array_almost_equal(reg.y[0],y,4)
x = np.array([[ 1. , 4. , 148. , 11.25, 0. , 0. , 0. ,
0. ]])
np.testing.assert_array_almost_equal(reg.x[0].toarray(),x,4)
e = np.array([ 29.45407124])
np.testing.assert_array_almost_equal(reg.e_pred[0],e,4)
my = 44.307180094786695
self.assertAlmostEqual(reg.mean_y,my)
sy = 23.606076835380495
self.assertAlmostEqual(reg.std_y,sy)
vm = np.array([ 47.42000914, 2.39526578, 0.00506895, 0.06480022,
69.67653371, 3.20661492, 0.01156766, 0.04862014, 0.00400775])
np.testing.assert_array_almost_equal(reg.vm.diagonal(),vm,4)
sig2 = 200.04433357145007
self.assertAlmostEqual(reg.sig2,sig2,4)
pr2 = 0.6404460298085746
self.assertAlmostEqual(reg.pr2,pr2)
std_err = np.array([ 6.88621878, 1.54766462, 0.07119654, 0.25455888, 8.34724707,
1.79070235, 0.10755305, 0.22049975, 0.0633068 ])
np.testing.assert_array_almost_equal(reg.std_err,std_err,4)
logll = -864.98505596489736
self.assertAlmostEqual(reg.logll,logll,4)
aic = 1747.9701119297947
self.assertAlmostEqual(reg.aic,aic,4)
schwarz = 1778.1368351310794
self.assertAlmostEqual(reg.schwarz,schwarz,4)
chow_r = np.array([[ 1.00180776, 0.31687348],
[ 0.05904944, 0.8080047 ],
[ 1.16987812, 0.27942629],
[ 1.95931177, 0.16158694]])
np.testing.assert_array_almost_equal(reg.chow.regi,chow_r,4)
chow_j = 21.648337464039283
self.assertAlmostEqual(reg.chow.joint[0],chow_j,4)