def test_regression(self):
y = self.endog
x = self.exog
n_groups, k_vars = self.dgp.n_groups, self.dgp.k_vars
R = np.c_[np.zeros((n_groups, k_vars - 1)), np.eye(n_groups)]
r = np.zeros(n_groups)
R = np.c_[np.zeros((n_groups - 1, k_vars)),
np.eye(n_groups - 1) - 1. / n_groups * np.ones(
(n_groups - 1, n_groups - 1))]
r = np.zeros(n_groups - 1)
R[:, k_vars - 1] = -1
lambd = 1 #1e-4
mod = TheilGLS(y, x, r_matrix=R, q_matrix=r, sigma_prior=lambd)
res = mod.fit()
# regression test
params1 = np.array([
0.96518694, 1.06152005, 0.31844136, 3.02747485, 3.25308031,
3.76229199, 1.99795797, 3.9831158, 3.1055317, 1.91599103,
4.5354633, 4.14332517, 3.69462963, 3.79567255, 2.18633118,
2.02848738, 3.74269763, 3.60041509, 3.27734962, 2.47771329,
3.23858674, 4.2973348, 3.98013994, 3.73415254, 2.88870379,
3.91311563, 3.71043309, 1.80506601, 3.78067131, 1.77164485,
3.88247, 3.28328127, 3.1313951, 3.03006754, 3.31012921, 3.08761618,
2.96735903, 1.54005178, 1.27778498, 1.47949121, 4.87184321,
3.03812406, 3.43574332, 2.16983158, 4.45339409, 2.64502381,
4.04767553, 4.42282326, 2.40153298, 3.55409206, 2.71256315,
3.32197196, 3.56054788, 2.58639318, 0.96230275, 1.8382348,
2.30788361, 2.49415769, 0.74777288, 3.04014659, 1.82256153,
4.89165865
])
assert_allclose(res.params, params1)
pen_weight_aicc = mod.select_pen_weight(method='aicc')
pen_weight_gcv = mod.select_pen_weight(method='gcv')
pen_weight_cv = mod.select_pen_weight(method='cv')
pen_weight_bic = mod.select_pen_weight(method='bic')
assert_allclose(pen_weight_gcv, pen_weight_aicc, rtol=0.1)
# regression tests:
assert_allclose(pen_weight_aicc, 2.98779297, rtol=1e-4)
assert_allclose(pen_weight_gcv, 2.69970703, rtol=1e-4)
assert_allclose(pen_weight_bic, 5.76005859, rtol=1e-4)
assert_allclose(pen_weight_cv, 1.3, rtol=1e-4)
def test_regression(self):
y = self.endog
x = self.exog
n_groups, k_vars = self.dgp.n_groups, self.dgp.k_vars
R = np.c_[np.zeros((n_groups, k_vars-1)), np.eye(n_groups)]
r = np.zeros(n_groups)
R = np.c_[np.zeros((n_groups-1, k_vars)),
np.eye(n_groups-1)-1./n_groups * np.ones((n_groups-1, n_groups-1))]
r = np.zeros(n_groups-1)
R[:, k_vars-1] = -1
lambd = 1 #1e-4
mod = TheilGLS(y, x, r_matrix=R, q_matrix=r, sigma_prior=lambd)
res = mod.fit()
# regression test
params1 = np.array([
0.96518694, 1.06152005, 0.31844136, 3.02747485, 3.25308031,
3.76229199, 1.99795797, 3.9831158 , 3.1055317 , 1.91599103,
4.5354633 , 4.14332517, 3.69462963, 3.79567255, 2.18633118,
2.02848738, 3.74269763, 3.60041509, 3.27734962, 2.47771329,
3.23858674, 4.2973348 , 3.98013994, 3.73415254, 2.88870379,
3.91311563, 3.71043309, 1.80506601, 3.78067131, 1.77164485,
3.88247 , 3.28328127, 3.1313951 , 3.03006754, 3.31012921,
3.08761618, 2.96735903, 1.54005178, 1.27778498, 1.47949121,
4.87184321, 3.03812406, 3.43574332, 2.16983158, 4.45339409,
2.64502381, 4.04767553, 4.42282326, 2.40153298, 3.55409206,
2.71256315, 3.32197196, 3.56054788, 2.58639318, 0.96230275,
1.8382348 , 2.30788361, 2.49415769, 0.74777288, 3.04014659,
1.82256153, 4.89165865])
assert_allclose(res.params, params1)
pen_weight_aicc = mod.select_pen_weight(method='aicc')
pen_weight_gcv = mod.select_pen_weight(method='gcv')
pen_weight_cv = mod.select_pen_weight(method='cv')
pen_weight_bic = mod.select_pen_weight(method='bic')
assert_allclose(pen_weight_gcv, pen_weight_aicc, rtol=0.1)
# regression tests:
assert_allclose(pen_weight_aicc, 2.98779297, rtol=1e-4)
assert_allclose(pen_weight_gcv, 2.69970703, rtol=1e-4)
assert_allclose(pen_weight_bic, 5.76005859, rtol=1e-4)
assert_allclose(pen_weight_cv, 1.3, rtol=1e-4)
def test_regression(self):
y = self.endog
x = self.exog
n_groups, k_vars = self.dgp.n_groups, self.dgp.k_vars
Rg = (np.eye(n_groups - 1) - 1. / n_groups * np.ones(
(n_groups - 1, n_groups - 1)))
R = np.c_[np.zeros((n_groups - 1, k_vars)), Rg]
r = np.zeros(n_groups - 1)
R[:, k_vars - 1] = -1
lambd = 1 #1e-4
mod = TheilGLS(y, x, r_matrix=R, q_matrix=r, sigma_prior=lambd)
res = mod.fit()
# regression test
params1 = np.array([
0.9751655, 1.05215277, 0.37135028, 2.0492626, 2.82062503,
2.82139775, 1.92940468, 2.96942081, 2.86349583, 3.20695368,
4.04516422, 3.04918839, 4.54748808, 3.49026961, 3.15529618,
4.25552932, 2.65471759, 3.62328747, 3.07283053, 3.49485898,
3.42301424, 2.94677593, 2.81549427, 2.24895113, 2.29222784,
2.89194946, 3.17052308, 2.37754241, 3.54358533, 3.79838425,
1.91189071, 1.15976407, 4.05629691, 1.58556827, 4.49941666,
4.08608599, 3.1889269, 2.86203652, 3.06785013, 1.9376162,
2.90657681, 3.71910592, 3.15607617, 3.58464547, 2.15466323,
4.87026717, 2.92909833, 2.64998337, 2.891171, 4.04422964,
3.54616122, 4.12135273, 3.70232028, 3.8314497, 2.2591451,
2.39321422, 3.13064532, 2.1569678, 2.04667506, 3.92064689,
3.66243644, 3.11742725
])
assert_allclose(res.params, params1)
pen_weight_aicc = mod.select_pen_weight(method='aicc')
pen_weight_gcv = mod.select_pen_weight(method='gcv')
pen_weight_cv = mod.select_pen_weight(method='cv')
pen_weight_bic = mod.select_pen_weight(method='bic')
assert_allclose(pen_weight_gcv, pen_weight_aicc, rtol=0.1)
# regression tests:
assert_allclose(pen_weight_aicc, 4.77333984, rtol=1e-4)
assert_allclose(pen_weight_gcv, 4.45546875, rtol=1e-4)
assert_allclose(pen_weight_bic, 9.35957031, rtol=1e-4)
assert_allclose(pen_weight_cv, 1.99277344, rtol=1e-4)
def test_regression(self):
y = self.endog
x = self.exog
n_groups, k_vars = self.dgp.n_groups, self.dgp.k_vars
Rg = (np.eye(n_groups-1) - 1. / n_groups *
np.ones((n_groups - 1, n_groups-1)))
R = np.c_[np.zeros((n_groups - 1, k_vars)), Rg]
r = np.zeros(n_groups - 1)
R[:, k_vars-1] = -1
lambd = 1 #1e-4
mod = TheilGLS(y, x, r_matrix=R, q_matrix=r, sigma_prior=lambd)
res = mod.fit()
# regression test
params1 = np.array([
0.9751655 , 1.05215277, 0.37135028, 2.0492626 , 2.82062503,
2.82139775, 1.92940468, 2.96942081, 2.86349583, 3.20695368,
4.04516422, 3.04918839, 4.54748808, 3.49026961, 3.15529618,
4.25552932, 2.65471759, 3.62328747, 3.07283053, 3.49485898,
3.42301424, 2.94677593, 2.81549427, 2.24895113, 2.29222784,
2.89194946, 3.17052308, 2.37754241, 3.54358533, 3.79838425,
1.91189071, 1.15976407, 4.05629691, 1.58556827, 4.49941666,
4.08608599, 3.1889269 , 2.86203652, 3.06785013, 1.9376162 ,
2.90657681, 3.71910592, 3.15607617, 3.58464547, 2.15466323,
4.87026717, 2.92909833, 2.64998337, 2.891171 , 4.04422964,
3.54616122, 4.12135273, 3.70232028, 3.8314497 , 2.2591451 ,
2.39321422, 3.13064532, 2.1569678 , 2.04667506, 3.92064689,
3.66243644, 3.11742725])
assert_allclose(res.params, params1)
pen_weight_aicc = mod.select_pen_weight(method='aicc')
pen_weight_gcv = mod.select_pen_weight(method='gcv')
pen_weight_cv = mod.select_pen_weight(method='cv')
pen_weight_bic = mod.select_pen_weight(method='bic')
assert_allclose(pen_weight_gcv, pen_weight_aicc, rtol=0.1)
# regression tests:
assert_allclose(pen_weight_aicc, 4.77333984, rtol=1e-4)
assert_allclose(pen_weight_gcv, 4.45546875, rtol=1e-4)
assert_allclose(pen_weight_bic, 9.35957031, rtol=1e-4)
assert_allclose(pen_weight_cv, 1.99277344, rtol=1e-4)