

def _forecast_error(self, steps):
    sigma2 = self.sigma2
    ma_rep = arma2ma(np.r_[(1, (- self.arparams))], np.r_[(1, fcerr.maparams)], nobs=steps)
    fcerr = np.sqrt((np.cumsum((cumsum_n(ma_rep, self.k_diff) ** 2)) * sigma2))
    return fcerr

dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/tsa/arima_model.py ARIMAResults._forecast_error/VarMisuse@45/56 `self`->`fcerr`