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A Bayesian model for binary Markov chains

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  • Souad Assoudou
  • Belkheir Essebbar

Abstract

This note is concerned with Bayesian estimation of the transition probabilities of a binary Markov chain observed from heterogeneous individuals. The model is founded on the Jeffreys' prior which allows for transition probabilities to be correlated. The Bayesian estimator is approximated by means of Monte Carlo Markov chain (MCMC) techniques. The performance of the Bayesian estimates is illustrated by analyzing a small simulated data set.

Suggested Citation

  • Souad Assoudou & Belkheir Essebbar, 2004. "A Bayesian model for binary Markov chains," International Journal of Mathematics and Mathematical Sciences, Hindawi, vol. 2004, pages 1-9, January.
    • Handle: RePEc:hin:jijmms:431391
    DOI: 10.1155/S0161171204202319
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    Cited by:

    1. Ye, Yuan & Lu, Yonggang & Robinson, Powell & Narayanan, Arunachalam, 2022. "An empirical Bayes approach to incorporating demand intermittency and irregularity into inventory control," European Journal of Operational Research, Elsevier, vol. 303(1), pages 255-272.

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