def _make_arma_names(data, k_trend, order, exog_names):
    k_ar, k_ma = order
    exog_names = exog_names or []
    ar_lag_names = util.make_lag_names([data.ynames], k_ar, 0)
    ar_lag_names = [''.join(('ar.', i)) for i in ar_lag_names]
    ma_lag_names = util.make_lag_names([data.ynames], k_ma, 0)
    ma_lag_names = [''.join(('ma.', i)) for i in ma_lag_names]
    trend_name = util.make_lag_names('', 0, k_trend)

    # ensure exog_names stays unchanged when the `fit` method
    # is called multiple times.
    if exog_names[-k_ma:] == ma_lag_names and \
       exog_names[-(k_ar+k_ma):-k_ma] == ar_lag_names and \
       (not exog_names or not trend_name and trend_name[0] == exog_names[0]):
        return exog_names

    exog_names = trend_name + exog_names + ar_lag_names + ma_lag_names
    return exog_names
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/tsa/arima_model.py/_make_arma_names/operator `or` -> `and`