A cross-validation filter for time series models

Piet De Jong

doi:10.1093/biomet/75.3.594

A cross-validation filter for time series models

Piet De Jong^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

37 Citations (Scopus)

Abstract

A filter is presented which computes cross-validation errors and associated statistics for an arbitrary state space model. The procedure is more efficient than an existing approach. Diffuse initial conditions are easily handled using a minor extension. The relationship to the fixed interval smoothing algorithm is investigated.

Original language	English
Pages (from-to)	594-600
Number of pages	7
Journal	Biometrika
Volume	75
Issue number	3
DOIs	https://doi.org/10.1093/biomet/75.3.594
Publication status	Published - Sep 1988
Externally published	Yes

Keywords

Cross-validation
Diffuse initial conditions
Kalman filter
Smoothing filter

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10.1093/biomet/75.3.594

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KW - Smoothing filter

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A cross-validation filter for time series models

Abstract

Keywords

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