def test_model_endog_regi_error(self):
#Columbus:
reg = SP.GM_Endog_Error_Het_Regimes(self.y,
self.X2,
self.yd,
self.q,
self.regimes,
self.w,
regime_err_sep=True)
betas = np.array([[7.92747424e+01], [5.78086230e+00],
[-3.83173581e+00],
[2.23210962e-01], [8.26255251e+01], [5.48294187e-01],
[-1.28432891e+00], [3.57661629e-02]])
np.testing.assert_allclose(reg.betas, betas, RTOL)
vm = np.array([
7.55988579e+02, 2.53659722e+02, -1.34288316e+02, -2.66141766e-01,
0.00000000e+00, 0.00000000e+00, 0.00000000e+00, 0.00000000e+00
])
np.testing.assert_allclose(reg.vm[0], vm, RTOL)
u = np.array([25.73781918])
np.testing.assert_allclose(reg.u[0], u, RTOL)
predy = np.array([-10.01183918])
np.testing.assert_allclose(reg.predy[0], predy, RTOL)
e = np.array([26.5449135])
np.testing.assert_allclose(reg.e_filtered[0], e, RTOL)
chow_r = np.array([[0.00998573, 0.92040097], [0.12660165, 0.72198192],
[0.12737281, 0.72117171], [0.43507956, 0.50950696]])
np.testing.assert_allclose(reg.chow.regi, chow_r, RTOL)
chow_j = 1.3756768204399892
np.testing.assert_allclose(reg.chow.joint[0], chow_j, RTOL)
#Artficial:
model = SP.GM_Endog_Error_Het_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)
model1 = GM_Endog_Error_Het(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_Endog_Error_Het(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_allclose(model.betas, tbetas, RTOL)
vm = np.hstack((model1.vm.diagonal(), model2.vm.diagonal()))
np.testing.assert_allclose(model.vm.diagonal(), vm, RTOL)
def test_model_endog(self):
reg = SP.GM_Endog_Error_Het_Regimes(self.y, self.X2, self.yd, self.q, self.regimes, self.w)
betas = np.array([[ 77.26679984],
[ 4.45992905],
[ 78.59534391],
[ 0.41432319],
[ -3.20196286],
[ -1.13672283],
[ 0.2174965 ]])
np.testing.assert_allclose(reg.betas,betas,RTOL)
u = np.array([ 20.50716917])
np.testing.assert_allclose(reg.u[0],u,RTOL)
e = np.array([ 25.13517175])
np.testing.assert_allclose(reg.e_filtered[0],e,RTOL)
predy = np.array([-4.78118917])
np.testing.assert_allclose(reg.predy[0],predy,RTOL)
n = 49
np.testing.assert_allclose(reg.n,n, RTOL)
k = 6
np.testing.assert_allclose(reg.k,k, RTOL)
y = np.array([ 15.72598])
np.testing.assert_allclose(reg.y[0],y,RTOL)
x = np.array([[ 0. , 0. , 1. , 19.531]])
np.testing.assert_allclose(reg.x[0].toarray(),x,RTOL)
yend = np.array([[ 0. , 80.467003]])
np.testing.assert_allclose(reg.yend[0].toarray(),yend,RTOL)
z = np.array([[ 0. , 0. , 1. , 19.531 , 0. ,
80.467003]])
np.testing.assert_allclose(reg.z[0].toarray(),z,RTOL)
my = 35.128823897959187
np.testing.assert_allclose(reg.mean_y,my, RTOL)
sy = 16.732092091229699
np.testing.assert_allclose(reg.std_y,sy, RTOL)
vm = np.array([ 509.66122149, 150.5845341 , 9.64413821, 5.54782831,
-80.95846045, -2.25308524, -3.2045214 ])
np.testing.assert_allclose(reg.vm[0],vm,RTOL)
pr2 = 0.19776512679331681
np.testing.assert_allclose(reg.pr2,pr2)
std_err = np.array([ 22.57567765, 11.34616946, 17.43881791, 1.30953812,
5.4830829 , 0.74634612, 0.29973079])
np.testing.assert_allclose(reg.std_err,std_err,RTOL)
chow_r = np.array([[ 0.0022216 , 0.96240654],
[ 0.13127347, 0.7171153 ],
[ 0.14367307, 0.70465645]])
np.testing.assert_allclose(reg.chow.regi,chow_r,RTOL)
chow_j = 1.2329971019087163
np.testing.assert_allclose(reg.chow.joint[0],chow_j, RTOL)