def test_from_formula(): mod = RecursiveLS.from_formula('cpi ~ m1', data=dta) res = mod.fit() # Test the RLS estimates against OLS estimates mod_ols = OLS.from_formula('cpi ~ m1', data=dta) res_ols = mod_ols.fit() assert_allclose(res.params, res_ols.params)
def test_from_formula(): mod = RecursiveLS.from_formula('cpi ~ m1', data=dta) res = mod.fit() # Test the RLS estimates against OLS estimates mod_ols = OLS.from_formula('cpi ~ m1', data=dta) res_ols = mod_ols.fit() assert_allclose(res.params, res_ols.params)
def test_from_formula(): with pytest.warns(ValueWarning, match="No frequency information"): mod = RecursiveLS.from_formula('cpi ~ m1', data=dta) res = mod.fit() # Test the RLS estimates against OLS estimates mod_ols = OLS.from_formula('cpi ~ m1', data=dta) res_ols = mod_ols.fit() assert_allclose(res.params, res_ols.params)
def test_from_formula(): with pytest.warns(ValueWarning, match="No frequency information"): mod = RecursiveLS.from_formula('cpi ~ m1', data=dta) res = mod.fit() # Test the RLS estimates against OLS estimates mod_ols = OLS.from_formula('cpi ~ m1', data=dta) res_ols = mod_ols.fit() assert_allclose(res.params, res_ols.params)