A cross-validation filter for time series models

Piet De Jong*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

36 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 languageEnglish
Pages (from-to)594-600
Number of pages7
JournalBiometrika
Volume75
Issue number3
DOIs
Publication statusPublished - Sep 1988
Externally publishedYes

Keywords

  • Cross-validation
  • Diffuse initial conditions
  • Kalman filter
  • Smoothing filter

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