DISTURBANCE SMOOTHER FOR STATE-SPACE MODELS

被引：22
|
作者：
KOOPMAN, SJ
机构：
来源：
BIOMETRIKA | 1993年 / 80卷 / 01期
关键词：
DISTURBANCE SMOOTHER; EM ALGORITHM; KALMAN FILTER; RESIDUAL; STATE SMOOTHER; STATE SPACE MODEL; UNOBSERVED COMPONENTS TIME SERIES MODEL;
D O I：
10.2307/2336762
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
This paper develops a method to evaluate the smoothed estimator of the disturbance vector in a state space model together with its mean squared error matrix. This disturbance smoother also leads to an efficient smoother for the state vector. Applications include a method to calculate auxiliary residuals for unobserved components time series models and an EM algorithm for estimating covariance parameters in a state space model.
引用
收藏
页码：117 / 126
页数：10
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