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