@classmethod
    def setupClass(cls):
        from statsmodels.datasets.longley import load
        dta = load()
        dta.exog = add_constant(dta.exog, prepend=True)
        wls_scalar = WLS(dta.endog, dta.exog, weights=1./3).fit()
        weights = [1/3.] * len(dta.endog)
        wls_array = WLS(dta.endog, dta.exog, weights=weights).fit()
        cls.res1 = wls_scalar
        cls.res2 = wls_array

#class TestWLS_GLS(CheckRegressionResults):
#    @classmethod
#    def setupClass(cls):
#        from statsmodels.datasets.ccard import load
#        data = load()
#        cls.res1 = WLS(data.endog, data.exog, weights = 1/data.exog[:,2]).fit()
#        cls.res2 = GLS(data.endog, data.exog, sigma = data.exog[:,2]).fit()
#
#    def check_confidenceintervals(self, conf1, conf2):
#        assert_almost_equal(conf1, conf2(), DECIMAL_4)
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/regression/tests/test_regression.py/TestWLSScalarVsArray.setupClass/original