reconnect moved files to git repo

venv/lib/python3.11/site-packages/statsmodels/regression/tests/test_cov.py

@@ -0,0 +1,38 @@
+"""Example: minimal OLS
+
+"""
+
+import numpy as np
+from numpy.testing import assert_almost_equal, assert_allclose
+
+import statsmodels.api as sm
+
+
+def test_HC_use():
+    np.random.seed(0)
+    nsample = 100
+    x = np.linspace(0,10, 100)
+    X = sm.add_constant(np.column_stack((x, x**2)), prepend=False)
+    beta = np.array([1, 0.1, 10])
+    y = np.dot(X, beta) + np.random.normal(size=nsample)
+
+    results = sm.OLS(y, X).fit()
+
+    # test cov_params
+    idx = np.array([1, 2])
+    cov12 = results.cov_params(column=[1, 2], cov_p=results.cov_HC0)
+    assert_almost_equal(cov12, results.cov_HC0[idx[:, None], idx], decimal=15)
+
+    #test t_test
+    tvals = results.params/results.HC0_se
+    ttest = results.t_test(np.eye(3), cov_p=results.cov_HC0)
+    assert_almost_equal(ttest.tvalue, tvals, decimal=14)
+    assert_almost_equal(ttest.sd, results.HC0_se, decimal=14)
+
+    #test f_test
+    ftest = results.f_test(np.eye(3)[:-1], cov_p=results.cov_HC0)
+    slopes = results.params[:-1]
+    idx = np.array([0,1])
+    cov_slopes = results.cov_HC0[idx[:,None], idx]
+    fval = np.dot(slopes, np.dot(np.linalg.inv(cov_slopes), slopes))/len(idx)
+    assert_allclose(ftest.fvalue, fval, rtol=12)