Note on the Linearity of Bayesian Estimates  in the Dependent Case

Souad Assoudou; Belkheir Essebbar

doi:10.4236/am.2014.51006

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Applied Mathematics > Vol.5 No.1, January 2014

Note on the Linearity of Bayesian Estimates in the Dependent Case ()

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 PDF HTML XML 2,824 Downloads 4,094 Views

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

Share and Cite:

S. Assoudou and B. Essebbar, "Note on the Linearity of Bayesian Estimates in the Dependent Case," Applied Mathematics, Vol. 5 No. 1, 2014, pp. 47-54. doi: 10.4236/am.2014.51006.

Conflicts of Interest

The authors declare no conflicts of interest.

References

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