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May, 1976 Empirical Bayes Estimation of a Distribution Function
Ramesh M. Korwar, Myles Hollander
Ann. Statist. 4(3): 581-588 (May, 1976). DOI: 10.1214/aos/1176343463

Abstract

A sequence of empirical Bayes estimators is defined for estimating a distribution function. The sequence is shown to be asymptotically optimal relative to a Ferguson Dirichlet process prior. Exact risk expressions are derived and the rate, at which the overall expected loss approaches the minimum Bayes risk, is exhibited. The empirical Bayes approach, based on the Dirichlet process, is also applied to the problem of estimating the mean of a distribution.

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Ramesh M. Korwar. Myles Hollander. "Empirical Bayes Estimation of a Distribution Function." Ann. Statist. 4 (3) 581 - 588, May, 1976. https://doi.org/10.1214/aos/1176343463

Information

Published: May, 1976
First available in Project Euclid: 12 April 2007

zbMATH: 0358.62035
MathSciNet: MR413388
Digital Object Identifier: 10.1214/aos/1176343463

Subjects:
Primary: 62G05
Secondary: 62C99

Keywords: Dirichlet process , distribution function , empirical Bayes estimator

Rights: Copyright © 1976 Institute of Mathematical Statistics

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Vol.4 • No. 3 • May, 1976
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