def xbetas(self, params):

        res = np.empty((self.nobs, self.nchoices))
        for choiceind in range(self.nchoices):
            res[:,choiceind] = np.dot(self.exog_bychoices[choiceind],
                                      params[self.beta_indices[choiceind]])
        return res
Predict using the Gaussian process regression model
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/sandbox/regression/runmnl.py/TryNCLogit.xbetas--crossover with--dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/gaussian_process/gpr.py/GaussianProcessRegressor.predict