Exact inference for continuous time markov chain models

John Geweke, Robert Clifford Marshall, Gary A. Zarkin

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Methods for exact Bayesian inference under a uniform diffuse prior are set forth for the continuous time homogeneous Markov chain model. It is shown how the exact posterior distribution of any function of interest may be computed using Monte Carlo integration. The solution handles the problems of embeddability in a very natural way, and provides (to our knowledge) the only solution that systematically takes this problem into account. The methods are illustrated using several sets of data.

Original languageEnglish (US)
Pages (from-to)653-669
Number of pages17
JournalReview of Economic Studies
Volume53
Issue number4
DOIs
StatePublished - Jan 1 1986

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Continuous-time Markov chain
Exact inference
Markov chain model
Monte Carlo integration
Posterior distribution
Bayesian inference

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics

Cite this

Geweke, John ; Marshall, Robert Clifford ; Zarkin, Gary A. / Exact inference for continuous time markov chain models. In: Review of Economic Studies. 1986 ; Vol. 53, No. 4. pp. 653-669.
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Exact inference for continuous time markov chain models. / Geweke, John; Marshall, Robert Clifford; Zarkin, Gary A.

In: Review of Economic Studies, Vol. 53, No. 4, 01.01.1986, p. 653-669.

Research output: Contribution to journalArticle

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