statsmodels.tsa.statespace.kalman_smoother.SmootherResults.predict¶

SmootherResults.
predict
(start=None, end=None, dynamic=None, **kwargs)¶ Insample and outofsample prediction for state space models generally
 Parameters
 start
int
,optional
Zeroindexed observation number at which to start prediction, i.e., the first prediction will be at start.
 end
int
,optional
Zeroindexed observation number at which to end prediction, i.e., the last prediction will be at end.
 dynamic
int
,optional
Offset relative to start at which to begin dynamic prediction. Prior to this observation, true endogenous values will be used for prediction; starting with this observation and continuing through the end of prediction, predicted endogenous values will be used instead.
 **kwargs
If the prediction range is outside of the sample range, any of the state space representation matrices that are timevarying must have updated values provided for the outofsample range. For example, of obs_intercept is a timevarying component and the prediction range extends 10 periods beyond the end of the sample, a (k_endog x 10) matrix must be provided with the new intercept values.
 start
 Returns
 results
kalman_filter.PredictionResults
A PredictionResults object.
 results
Notes
All prediction is performed by applying the deterministic part of the measurement equation using the predicted state variables.
Outofsample prediction first applies the Kalman filter to missing data for the number of periods desired to obtain the predicted states.