On computing the expected Fisher information matrix for state-space model parameters

被引：19
|
作者：
Cavanaugh, JE
Shumway, RH
机构：
[1] UNIV MISSOURI,DEPT STAT,COLUMBIA,MO 65211
[2] UNIV CALIF DAVIS,DIV STAT,DAVIS,CA 95616
来源：
STATISTICS & PROBABILITY LETTERS | 1996年 / 26卷 / 04期
关键词：
EM algorithm; Kalman filter; recursive algorithm; time series;
D O I：
10.1016/0167-7152(95)00031-3
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
A general, recursive algorithm is presented for computing the expected Fisher information matrix for state-space model parameters. Simulation results are featured where known Fisher information matrices corresponding to simple state-space models are estimated using both observed and expected information matrices. The accuracy of the two approaches is compared.
引用
收藏
页码：347 / 355
页数：9
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