Open Access
June, 1993 On Equivariance and the Compound Decision Problem
Mostafa Mashayekhi
Ann. Statist. 21(2): 736-745 (June, 1993). DOI: 10.1214/aos/1176349147

Abstract

This paper obtains some extensions of Gilliland and Hannan's results on equivariance and the compound decision problem. Consider a compound decision problem with restricted component risk and component distributions in a norm compact set of mutually absolutely continuous probability measures. Then the method of proof of a theorem of Gilliland and Hannan translates the results of Mashayekhi on symmetrization of product measures into uniform convergence to zero of the excess of the simple envelop over the equivariant envelope. Our envelope results strengthen, among other things, the results of Datta who obtained admissible asymptotically optimal solutions to the compound estimation problem for a large subclass of the real one parameter exponential family under squared error loss. Sufficient conditions for asymptotic optimality of "delete bootstrap" rules are given and, for squared error loss estimation of continuous functions and for finite action space problems with continuous loss functions, the problem of treating the asymptotic excess compound risk of Bayes compound rules is reduced to the question of $L_1$-consistency of certain mixtures. Examples of estimates satisfying the above consistency condition are provided.

Citation

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Mostafa Mashayekhi. "On Equivariance and the Compound Decision Problem." Ann. Statist. 21 (2) 736 - 745, June, 1993. https://doi.org/10.1214/aos/1176349147

Information

Published: June, 1993
First available in Project Euclid: 12 April 2007

zbMATH: 0797.62006
MathSciNet: MR1232515
Digital Object Identifier: 10.1214/aos/1176349147

Subjects:
Primary: 62C25
Secondary: 62A05

Keywords: Asymptotically optimal , compound decision , consistent mixtures , delete bootstraps rules , Equivariance , equivariant envelope , minimum distance , simple envelope

Rights: Copyright © 1993 Institute of Mathematical Statistics

Vol.21 • No. 2 • June, 1993
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