def _opt_wtd_nuis_regress(self, test_vals):
        test_params = test_vals.reshape(self.model.nvar, 1)
        est_vect = self.model.uncens_exog * (self.model.uncens_endog -
                                            np.dot(self.model.uncens_exog,
                                                         test_params))
        eta_star = self._modif_newton(np.zeros(self.model.nvar), est_vect,
                                         self.model._fit_weights)
        denom = np.sum(self.model._fit_weights) + np.dot(eta_star, est_vect.T)
        self.new_weights = self.model._fit_weights / denom
        return -1 * np.sum(np.log(self.new_weights))
A function that is optimized over nuisance parameters to conduct a
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/emplike/aft_el.py/OptAFT._opt_wtd_nuis_regress