Disturbance smoother for state space models

Siem Jan Koopman

doi:10.1093/biomet/80.1.117

Disturbance smoother for state space models

Siem Jan Koopman^*

^*Corresponding author for this work

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

SUMMARY: 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.

Original language	English
Pages (from-to)	117-126
Number of pages	10
Journal	Biometrika
Volume	80
Issue number	1
DOIs	https://doi.org/10.1093/biomet/80.1.117
Publication status	Published - 1 Mar 1993
Externally published	Yes

Keywords

Disturbance smoother
EM algorithm
Kalman filter
Residual
State smoother
State space model
Unobserved components time series model

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10.1093/biomet/80.1.117

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title = "Disturbance smoother for state space models",

abstract = "SUMMARY: 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.",

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year = "1993",

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doi = "10.1093/biomet/80.1.117",

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AB - SUMMARY: 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.

KW - Disturbance smoother

KW - EM algorithm

KW - Kalman filter

KW - Residual

KW - State smoother

KW - State space model

KW - Unobserved components time series model

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DO - 10.1093/biomet/80.1.117

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VL - 80

SP - 117

EP - 126

JO - Biometrika

JF - Biometrika

IS - 1

ER -

Disturbance smoother for state space models

Abstract

Keywords

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