get a dict of prior prediction variances

        Returns
        -------
        prior_prediction : dict
            dictionary of prediction name, prior variance pairs

def prior_prediction(self):
        """get a dict of prior prediction variances

        Returns
        -------
        prior_prediction : dict
            dictionary of prediction name, prior variance pairs

        """
        if self.__prior_prediction is not None:
            return self.__prior_prediction
        else:
            if self.predictions is not None:
                self.log("propagating prior to predictions")
                prior_cov = self.predictions.T *\
                                self.parcov * self.predictions
                self.__prior_prediction = {n:v for n,v in
                                          zip(prior_cov.row_names,
                                              np.diag(prior_cov.x))}
                self.log("propagating prior to predictions")
            else:
                self.__prior_prediction = {}
            return self.__prior_prediction