statsmodels.tsa.ar_model.ARResults.predict

ARResults.predict(start=None, end=None, dynamic=False)

Returns in-sample and out-of-sample prediction.

Parameters:

start : int, str, or datetime

Zero-indexed observation number at which to start forecasting, ie., the first forecast is start. Can also be a date string to parse or a datetime type.

end : int, str, or datetime

Zero-indexed observation number at which to end forecasting, ie., the first forecast is start. Can also be a date string to parse or a datetime type.

dynamic : bool

The dynamic keyword affects in-sample prediction. If dynamic is False, then the in-sample lagged values are used for prediction. If dynamic is True, then in-sample forecasts are used in place of lagged dependent variables. The first forecasted

confint : bool, float

Whether to return confidence intervals. If confint == True, 95 % confidence intervals are returned. Else if confint is a float, then it is assumed to be the alpha value of the confidence interval. That is confint == .05 returns a 95% confidence interval, and .10 would return a 90% confidence interval. value is start.

Returns:

predicted values : array

Notes

The linear Gaussian Kalman filter is used to return pre-sample fitted values. The exact initial Kalman Filter is used. See Durbin and Koopman in the references for more information.