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2013•Journal of Hefei University of TechnologyRequires access

Bayes Empirical Bayes estimation for the parameter of Rayleigh distribution

Lin Liu

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Abstract

In this paper,Bayes Empirical Bayes estimation for the parameter of Rayleigh distribution family is considered under squared loss function.It is proved that the Bayes Empirical Bayes estimation converges almost surely to Bayes estimation and it is asymptotically optimal under the condition that b=1.And a Monte Carlo stochastic simulation experiment is given to verify the asymptotically optimal property of the Bayes Empirical Bayes estimation.

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What this paper is about

In this paper,Bayes Empirical Bayes estimation for the parameter of Rayleigh distribution family is considered under squared loss function.It is proved that the Bayes Empirical Bayes estimation converges almost surely to Bayes estimation and it is asymptotically optimal under the condition that b=1.And a Monte Carlo stochastic simulation experiment is given to verify the asymptotically optimal property of the Bayes Empirical Bayes estimation.

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Available abstract

In this paper,Bayes Empirical Bayes estimation for the parameter of Rayleigh distribution family is considered under squared loss function.It is proved that the Bayes Empirical Bayes estimation converges almost surely to Bayes estimation and it is asymptotically optimal under the condition that b=1.And a Monte Carlo stochastic simulation experiment is given to verify the asymptotically optimal property of the Bayes Empirical Bayes estimation.

Key concepts: Bayes' theorem, Bayes error rate, Bayes estimator, Rayleigh distribution, Mathematics, Bayes' rule, Bayes factor, Asymptotically optimal algorithm

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