Bayesian estimation of hidden Markov chains: a stochastic implementation

Christian P. Robert, Gilles Celeux and Jean Diebolt

Statistics & Probability Letters, 1993, vol. 16, issue 1, 77-83

Abstract: Hidden Markov models lead to intricate computational problems when considered directly. In this paper, we propose an approximation method based on Gibbs sampling which allows an effective derivation of Bayes estimators for these models.

Keywords: Gibbs; sampling; forward--backward; recursion; formula; ergodicity; stochastic; restoration; geometric; convergence (search for similar items in EconPapers)
Date: 1993
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Citations: View citations in EconPapers (15)

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