def test_n_k(self):
X = []
X.append(self.db.by_col("INC"))
X.append(self.db.by_col("CRIME"))
self.X = np.array(X).T
yd2, q2 = spreg.utils.set_endog(self.y, self.X, self.w, None, None, 2,
True)
self.X = np.hstack((np.ones(self.y.shape), self.X))
self.X = SP.csr_matrix(self.X)
reg = BaseGM_Lag(self.y,
self.X,
yend=yd2,
q=q2,
w=self.w,
w_lags=2,
sig2n_k=True)
betas = np.array([[4.53017056e+01], [6.20888617e-01],
[-4.80723451e-01], [2.83622122e-02]])
np.testing.assert_allclose(reg.betas, betas, RTOL)
vm = np.array([
[
3.49389596e+02, -5.36394351e+00, -2.81960968e+00,
-4.35694515e+00
],
[-5.36394351e+00, 2.99965892e-01, 6.44054000e-02, -3.13108972e-02],
[-2.81960968e+00, 6.44054000e-02, 3.61800155e-02, 1.61095854e-02],
[-4.35694515e+00, -3.13108972e-02, 1.61095854e-02, 1.09698285e-01]
])
np.testing.assert_allclose(reg.vm, vm, RTOL)
def test_init_hac_(self):
X = []
X.append(self.db.by_col("INC"))
X.append(self.db.by_col("CRIME"))
self.X = np.array(X).T
yd2, q2 = spreg.utils.set_endog(self.y, self.X, self.w, None, None, 2,
True)
self.X = np.hstack((np.ones(self.y.shape), self.X))
self.X = SP.csr_matrix(self.X)
gwk = libpysal.weights.Kernel.from_shapefile(
libpysal.examples.get_path('columbus.shp'),
k=15,
function='triangular',
fixed=False)
base_gm_lag = BaseGM_Lag(self.y,
self.X,
yend=yd2,
q=q2,
w=self.w,
w_lags=2,
robust='hac',
gwk=gwk)
tbetas = np.array([[4.53017056e+01], [6.20888617e-01],
[-4.80723451e-01], [2.83622122e-02]])
np.testing.assert_allclose(base_gm_lag.betas, tbetas)
dbetas = D.se_betas(base_gm_lag)
se_betas = np.array([19.08513569, 0.51769543, 0.18244862, 0.35460553])
np.testing.assert_allclose(dbetas, se_betas)
def test_init_white_(self):
w_lags = 2
X = []
X.append(self.db.by_col("INC"))
X.append(self.db.by_col("CRIME"))
self.X = np.array(X).T
#yd2, q2 = spreg.utils.set_endog(self.y, self.X, self.w, None, None, w_lags, True)
self.X = np.hstack((np.ones(self.y.shape),self.X))
base_gm_lag = BaseGM_Lag(self.y, self.X, w=self.w, w_lags=w_lags, robust='white')
tbetas = np.array([[ 4.53017056e+01], [ 6.20888617e-01], [ -4.80723451e-01], [ 2.83622122e-02]])
np.testing.assert_allclose(base_gm_lag.betas, tbetas)
dbetas = D.se_betas(base_gm_lag)
se_betas = np.array([ 20.47077481, 0.50613931, 0.20138425, 0.38028295 ])
np.testing.assert_allclose(dbetas, se_betas)
def test_lag_q(self):
w_lags = 2
X = np.array(self.db.by_col("INC"))
self.X = np.reshape(X, (49,1))
yd = np.array(self.db.by_col("CRIME"))
yd = np.reshape(yd, (49,1))
q = np.array(self.db.by_col("DISCBD"))
q = np.reshape(q, (49,1))
#yd2, q2 = spreg.utils.set_endog(self.y, self.X, self.w, yd, q, w_lags, False)
self.X = np.hstack((np.ones(self.y.shape),self.X))
reg = BaseGM_Lag(self.y, self.X, w=self.w, yend=yd, q=q, w_lags=w_lags, lag_q=False)
tbetas = np.array( [[ 108.83261383], [ -0.48041099], [ -1.18950006], [ -0.56140186]])
np.testing.assert_allclose(tbetas, reg.betas)
dbetas = D.se_betas(reg)
se_betas = np.array([ 58.33203837, 1.09100446, 0.62315167, 0.68088777])
np.testing.assert_allclose(dbetas, se_betas)
def test_init_discbd(self):
w_lags = 2
X = np.array(self.db.by_col("INC"))
self.X = np.reshape(X, (49,1))
yd = np.array(self.db.by_col("CRIME"))
yd = np.reshape(yd, (49,1))
q = np.array(self.db.by_col("DISCBD"))
q = np.reshape(q, (49,1))
#yd2, q2 = spreg.utils.set_endog(self.y, self.X, self.w, yd, q, w_lags, True)
self.X = np.hstack((np.ones(self.y.shape),self.X))
reg = BaseGM_Lag(self.y, self.X, w=self.w, yend=yd, q=q, w_lags=w_lags)
tbetas = np.array([[ 100.79359082], [ -0.50215501], [ -1.14881711], [ -0.38235022]])
np.testing.assert_allclose(tbetas, reg.betas)
dbetas = D.se_betas(reg)
se_betas = np.array([ 53.0829123 , 1.02511494, 0.57589064, 0.59891744 ])
np.testing.assert_allclose(dbetas, se_betas)
def test___init__(self):
X = []
X.append(self.db.by_col("INC"))
X.append(self.db.by_col("CRIME"))
self.X = np.array(X).T
yd2, q2 = spreg.utils.set_endog(self.y, self.X, self.w, None, None, 2,
True)
self.X = np.hstack((np.ones(self.y.shape), self.X))
self.X = SP.csr_matrix(self.X)
reg = BaseGM_Lag(self.y, self.X, yend=yd2, q=q2, w=self.w, w_lags=2)
betas = np.array([[4.53017056e+01], [6.20888617e-01],
[-4.80723451e-01], [2.83622122e-02]])
np.testing.assert_allclose(reg.betas, betas, RTOL)
h_0 = np.array([
1., 19.531, 15.72598, 18.594, 24.7142675, 13.72216667, 27.82929567
])
np.testing.assert_allclose(reg.h.toarray()[0], h_0)
hth = np.array([
49., 704.371999, 1721.312371, 724.7435916, 1707.35412945,
711.31248483, 1729.63201243
])
np.testing.assert_allclose(reg.hth[0], hth, RTOL)
hthi = np.array([
7.33701328e+00, 2.27764882e-02, 2.18153588e-02, -5.11035447e-02,
1.22515181e-03, -2.38079378e-01, -1.20149133e-01
])
np.testing.assert_allclose(reg.hthi[0], hthi, RTOL)
self.assertEqual(reg.k, 4)
self.assertEqual(reg.kstar, 1)
np.testing.assert_allclose(reg.mean_y, 38.436224469387746, RTOL)
self.assertEqual(reg.n, 49)
pfora1a2 = np.array(
[80.5588479, -1.06625281, -0.61703759, -1.10071931])
np.testing.assert_allclose(reg.pfora1a2[0], pfora1a2, RTOL)
predy_5 = np.array([[50.87411532], [50.76969931], [41.77223722],
[33.44262382], [28.77418036]])
np.testing.assert_allclose(reg.predy[0:5], predy_5, RTOL)
q_5 = np.array([18.594, 24.7142675, 13.72216667, 27.82929567])
np.testing.assert_allclose(reg.q[0], q_5)
np.testing.assert_allclose(reg.sig2n_k, 234.54258763039289, RTOL)
np.testing.assert_allclose(reg.sig2n, 215.39625394627919, RTOL)
np.testing.assert_allclose(reg.sig2, 215.39625394627919, RTOL)
np.testing.assert_allclose(reg.std_y, 18.466069465206047, RTOL)
u_5 = np.array([[29.59288768], [-6.20269831], [-15.42223722],
[-0.24262282], [-5.54918036]])
np.testing.assert_allclose(reg.u[0:5], u_5, RTOL)
np.testing.assert_allclose(reg.utu, 10554.41644336768, RTOL)
varb = np.array([
[
1.48966377e+00, -2.28698061e-02, -1.20217386e-02,
-1.85763498e-02
],
[-2.28698061e-02, 1.27893998e-03, 2.74600023e-04, -1.33497705e-04],
[-1.20217386e-02, 2.74600023e-04, 1.54257766e-04, 6.86851184e-05],
[-1.85763498e-02, -1.33497705e-04, 6.86851184e-05, 4.67711582e-04]
])
np.testing.assert_allclose(reg.varb, varb, RTOL)
vm = np.array([
[
3.20867996e+02, -4.92607057e+00, -2.58943746e+00,
-4.00127615e+00
],
[-4.92607057e+00, 2.75478880e-01, 5.91478163e-02, -2.87549056e-02],
[-2.58943746e+00, 5.91478163e-02, 3.32265449e-02, 1.47945172e-02],
[-4.00127615e+00, -2.87549056e-02, 1.47945172e-02, 1.00743323e-01]
])
np.testing.assert_allclose(reg.vm, vm, RTOL)
x_0 = np.array([1., 19.531, 15.72598])
np.testing.assert_allclose(reg.x.toarray()[0], x_0, RTOL)
y_5 = np.array([[80.467003], [44.567001], [26.35], [33.200001],
[23.225]])
np.testing.assert_allclose(reg.y[0:5], y_5, RTOL)
yend_5 = np.array([[35.4585005], [46.67233467], [45.36475125],
[32.81675025], [30.81785714]])
np.testing.assert_allclose(reg.yend[0:5], yend_5, RTOL)
z_0 = np.array([1., 19.531, 15.72598, 35.4585005])
np.testing.assert_allclose(reg.z.toarray()[0], z_0, RTOL)
zthhthi = np.array([[
1.00000000e+00, -2.22044605e-16, -2.22044605e-16, 2.22044605e-16,
4.44089210e-16, 0.00000000e+00, -8.88178420e-16
],
[
0.00000000e+00, 1.00000000e+00,
-3.55271368e-15, 3.55271368e-15,
-7.10542736e-15, 7.10542736e-14, 0.00000000e+00
],
[
1.81898940e-12, 2.84217094e-14, 1.00000000e+00,
0.00000000e+00, -2.84217094e-14,
5.68434189e-14, 5.68434189e-14
],
[
-8.31133940e+00, -3.76104678e-01,
-2.07028208e-01, 1.32618931e+00,
-8.04284562e-01, 1.30527047e+00, 1.39136816e+00
]])
#np.testing.assert_allclose(reg.zthhthi, zthhthi,RTOL)
np.testing.assert_array_almost_equal(reg.zthhthi, zthhthi, 7)