Note on the Linearity of Bayesian Estimates in the Dependent Case

Souad Assoudou, Belkheir Essebbar

Department of Economics, Faculty of Law, Economics and Social Sciences, Hassan I University, Settat, Morocco.
Department of Mathematics and Computer Sciences, Faculty of Science, Mohammed V University, Rabat, Morocco.

DOI: 10.4236/am.2014.51006                

Abstract

This work deals with the relationship between the Bayesian and the maximum likelihood estimators in case of dependent observations. In case of Markov chains, we show that the Bayesian estimator of the transition probabilities is a linear function of the maximum likelihood estimator (MLE).

Keywords

Bayes Estimator; Maximum Likelihood Estimator; Markov Chain; Transition Probabilities; Jeffreys’ Prior; Multivariate Beta Prior; MCMC

Conflicts of Interest

The authors declare no conflicts of interest.

References

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[3]	S. Assoudou and B. Essebbar, “A Bayesian Model for Markov Chains via Jeffreys’ Prior,” Department of Mathematics and Computer Sciences, Faculté des Sciences of Rabat, Morocco, 2001.
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