cf6a25ed5aae0f78e42b7b9594f54772880aaf53,linearmodels/panel/model.py,BetweenOLS,fit,#BetweenOLS#Any#Any#,510

Before Change

        self._avgx = x
        self._avgw = w
        if np.all(self.weights.values2d == 1.0) and not reweight:
            w = root_w = np.ones_like(w)
        else:
            root_w = np.sqrt(w)

        wx = root_w * x

After Change

        df_resid = nobs - df_model
        cov_denom = nobs if not debiased else df_resid
        cov_est = COVARIANCE_ESTIMATORS[cov_type]
        if cov_est not in self._supported_covs:
            raise ValueError("Requested covariance estimator is not supported for the model.")
        cov = cov_est(wy, wx, params, cov_denom, **cov_config)
        weps = wy - wx @ params
        eps = y - x @ params
        residual_ss = float(weps.T @ weps)

Instances