statsmodels.tsa.statespace.kalman_filter.PredictionResults¶

class
statsmodels.tsa.statespace.kalman_filter.
PredictionResults
(results, start, end, nstatic, ndynamic, nforecast)[source]¶ Results of insample and outofsample prediction for state space models generally
 Parameters
 results
FilterResults
Output from filtering, corresponding to the prediction desired
 start
int
Zeroindexed observation number at which to start forecasting, i.e., the first forecast will be at start.
 end
int
Zeroindexed observation number at which to end forecasting, i.e., the last forecast will be at end.
 nstatic
int
Number of insample static predictions (these are always the first elements of the prediction output).
 ndynamic
int
Number of insample dynamic predictions (these always follow the static predictions directly, and are directly followed by the forecasts).
 nforecast
int
Number of insample 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
Zeroindexed 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
Zeroindexed 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 insample static predictions.
 ndynamic
int
Number of insample dynamic predictions.
 nforecast
int
Number of insample 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 onestepahead 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
predict
([start, end, dynamic])Insample and outofsample 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
clear
Methods
clear
()predict
([start, end, dynamic])Insample and outofsample 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