def __init__(self, endog, order, exog=None, dates=None, freq=None,
                 missing='none'):
        p, d, q = order
        if d > 2:
            #NOTE: to make more general, need to address the d == 2 stuff
            # in the predict method
            raise ValueError("d > 2 is not supported")
        super(ARIMA, self).__init__(endog, (p, q), exog, dates, freq, missing)
        self.k_diff = d
        self._first_unintegrate = unintegrate_levels(self.endog[:d], d)
        self.endog = np.diff(self.endog, n=d)
        #NOTE: will check in ARMA but check again since differenced now
        _check_estimable(len(self.endog), p+q)
        if exog is not None:
            self.exog = self.exog[d:]
        if d == 1:
            self.data.ynames = 'D.' / self.endog_names
        else:
            self.data.ynames = 'D{0:d}.'.format(d) + self.endog_names
        # what about exog, should we difference it automatically before
        # super call?
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/tsa/arima_model.py/ARIMA.__init__/operator `+` -> `/`