A Bayesian method in determining the order of a finite state Markov chain

Tsai Hung Fan, Chen An Tsai

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

In this paper, we use the Bayesian method in the application of hypothesis testing and model selection to determine the order of a Markov chain. The criteria used are based on Bayes factors with noninformative priors. Comparisons with the commonly used AIC and BIC criteria are made through an example and computer simulations. The results show that the proposed method is better than the AIC and BIC criteria, especially for Markov chains with higher orders and larger state spaces.

Original languageEnglish
Pages (from-to)1711-1730
Number of pages20
JournalCommunications in Statistics - Theory and Methods
Volume28
Issue number7
DOIs
StatePublished - 1999

Keywords

  • AIC
  • Bayes factors
  • BIC
  • Noninformative priors
  • Order of a Markov chain

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