def _get_predict_end(self, end, dynamic=False):
        """
        Returns last index to be forecast of the differenced array.
        Handling of inclusiveness should be done in the predict function.
        """
        end, out_of_sample = super(ARIMA, self)._get_predict_end(end, dynamic)
        if 'mle' not in self.method and not dynamic:
            end -= self.k_ar

        return end + self.k_diff, out_of_sample
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/tsa/arima_model.py/ARIMA._get_predict_end/operator `-` -> `+`