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May, 1979 Empirical Bayes Estimation of a Binomial Parameter Via Mixtures of Dirichlet Processes
Donald A. Berry, Ronald Christensen
Ann. Statist. 7(3): 558-568 (May, 1979). DOI: 10.1214/aos/1176344677


The theory of Dirichlet processes is applied to the empirical Bayes estimation problem in the binomial case. The approach is Bayesian rather than being empirical Bayesian. When the prior is a Dirichlet process the posterior is a mixture of Dirichlet processes. Explicit estimators are given for the case of 2 and 3 parameters and compared with other empirical Bayes estimators by way of examples. Since the number of calculations become enormous when the number of parameters gets larger than 2 or 3 we propose two approximations for estimators of a particular parameter and compare their performance using examples.


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Donald A. Berry. Ronald Christensen. "Empirical Bayes Estimation of a Binomial Parameter Via Mixtures of Dirichlet Processes." Ann. Statist. 7 (3) 558 - 568, May, 1979.


Published: May, 1979
First available in Project Euclid: 12 April 2007

zbMATH: 0407.62018
MathSciNet: MR527491
Digital Object Identifier: 10.1214/aos/1176344677

Primary: 62C10
Secondary: 62F10 , 62F15

Keywords: approximating mixtures of Dirichlet processes , binomial parameter estimation , Dirichlet processes , empirical Bayes estimation , mixtures of Dirichlet processes

Rights: Copyright © 1979 Institute of Mathematical Statistics

Vol.7 • No. 3 • May, 1979
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