@cache_readonly
    def fittedvalues(self):
        model = self.model
        endog = model.endog.copy()
        k_ar = self.k_ar
        exog = model.exog  # this is a copy
        if exog is not None:
            if model.method == "css" and k_ar > 0:
                exog = exog[k_ar:]
        if model.method == "css" and k_ar > 0:
            endog = endog[k_ar:]
        fv = endog - self.resid
        # add deterministic part back in
        #k = self.k_exog + self.k_trend
        #TODO: this needs to be commented out for MLE with constant
        #if k != 0:
        #    fv += dot(exog, self.params[:k])
        return fv
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/tsa/arima_model.py/ARMAResults.fittedvalues/original