# statsmodels.tsa.ar_model.AR.predict¶

AR.predict(params, start=None, end=None, dynamic=False)[source]

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

Parameters
paramsndarray

The fitted model parameters.

startint, 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.

endint, 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.

dynamicbool

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 value is start.

Returns
array_like

An array containing the predicted values.

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.