Construct losses for the ensemble and each constitute model
        
        Parameters
        ----------
        data: np.ndarray
            The univariate time series

        predictions : np.ndarray
            The predictions of each constitute model

        ensemble_prediction : np.ndarray
            The prediction of the ensemble model

        Returns
        ----------
        - np.ndarray of the losses for each model

def _construct_losses(self, data, predictions, ensemble_prediction):
        """ Construct losses for the ensemble and each constitute model
        
        Parameters
        ----------
        data: np.ndarray
            The univariate time series

        predictions : np.ndarray
            The predictions of each constitute model

        ensemble_prediction : np.ndarray
            The prediction of the ensemble model

        Returns
        ----------
        - np.ndarray of the losses for each model
        """

        losses = []
        losses.append(self.loss_type(data, ensemble_prediction).sum()/data.shape[0])
        for model in range(len(self.model_list)):
            losses.append(self.loss_type(data, predictions[:,model]).sum()/data.shape[0])
        return losses