statsmodels.tsa.statespace.structural.UnobservedComponentsResults.get_prediction¶

UnobservedComponentsResults.
get_prediction
(start=None, end=None, dynamic=False, index=None, exog=None, **kwargs)[source]¶ Insample prediction and outofsample forecasting
Parameters:  start (int, str, or datetime, optional) – Zeroindexed 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. Default is the the zeroth observation.
 end (int, str, or datetime, optional) – Zeroindexed 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. However, if the dates index does not have a fixed frequency, end must be an integer index if you want out of sample prediction. Default is the last observation in the sample.
 exog (array_like, optional) – If the model includes exogenous regressors, you must provide exactly enough outofsample values for the exogenous variables if end is beyond the last observation in the sample.
 dynamic (boolean, int, str, or datetime, optional) – Integer offset relative to start at which to begin dynamic prediction. Can also be an absolute date string to parse or a datetime type (these are not interpreted as offsets). Prior to this observation, true endogenous values will be used for prediction; starting with this observation and continuing through the end of prediction, forecasted endogenous values will be used instead.
 full_results (boolean, optional) – If True, returns a FilterResults instance; if False returns a tuple with forecasts, the forecast errors, and the forecast error covariance matrices. Default is False.
 **kwargs – Additional arguments may required for forecasting beyond the end of the sample. See FilterResults.predict for more details.
Returns: forecast – Array of out of sample forecasts.
Return type: array