statsmodels.tsa.statespace.kalman_filter.PredictionResults¶
- class statsmodels.tsa.statespace.kalman_filter.PredictionResults(results, start, end, nstatic, ndynamic, nforecast, oos_results=None)[source]¶
Results of in-sample and out-of-sample prediction for state space models generally
- Parameters:
- results
FilterResults
Output from filtering, corresponding to the prediction desired
- start
int
Zero-indexed observation number at which to start forecasting, i.e., the first forecast will be at start.
- end
int
Zero-indexed observation number at which to end forecasting, i.e., the last forecast will be at end.
- nstatic
int
Number of in-sample static predictions (these are always the first elements of the prediction output).
- ndynamic
int
Number of in-sample dynamic predictions (these always follow the static predictions directly, and are directly followed by the forecasts).
- nforecast
int
Number of in-sample forecasts (these always follow the dynamic predictions directly).
- results
Notes
The provided ranges must be conformable, meaning that it must be that end - start == nstatic + ndynamic + nforecast.
This class is essentially a view to the FilterResults object, but returning the appropriate ranges for everything.
- Attributes:
- npredictions
int
Number of observations in the predicted series; this is not necessarily the same as the number of observations in the original model from which prediction was performed.
- start
int
Zero-indexed observation number at which to start prediction, i.e., the first predict will be at start; this is relative to the original model from which prediction was performed.
- end
int
Zero-indexed observation number at which to end prediction, i.e., the last predict will be at end; this is relative to the original model from which prediction was performed.
- nstatic
int
Number of in-sample static predictions.
- ndynamic
int
Number of in-sample dynamic predictions.
- nforecast
int
Number of in-sample forecasts.
- endog
ndarray
The observation vector.
- design
ndarray
The design matrix, \(Z\).
- obs_intercept
ndarray
The intercept for the observation equation, \(d\).
- obs_cov
ndarray
The covariance matrix for the observation equation \(H\).
- transition
ndarray
The transition matrix, \(T\).
- state_intercept
ndarray
The intercept for the transition equation, \(c\).
- selection
ndarray
The selection matrix, \(R\).
- state_cov
ndarray
The covariance matrix for the state equation \(Q\).
- filtered_state
ndarray
The filtered state vector at each time period.
- filtered_state_cov
ndarray
The filtered state covariance matrix at each time period.
- predicted_state
ndarray
The predicted state vector at each time period.
- predicted_state_cov
ndarray
The predicted state covariance matrix at each time period.
- forecasts
ndarray
The one-step-ahead forecasts of observations at each time period.
- forecasts_error
ndarray
The forecast errors at each time period.
- forecasts_error_cov
ndarray
The forecast error covariance matrices at each time period.
- npredictions
Methods
clear
()predict
([start, end, dynamic])In-sample and out-of-sample prediction for state space models generally
update_filter
(kalman_filter)Update the filter results
update_representation
(model[, only_options])Update the results to match a given model
Properties
Kalman gain matrices
Standardized forecast errors