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Optimal Convergence Rate of Empirical Bayes Tests for Uniform Distributions  

Liang, Ta-Chen (Department of mathematics, Wayne State University, Detroit, MI 48202, U. S. A.)
Publication Information
Journal of the Korean Statistical Society / v.31, no.1, 2002 , pp. 33-43 More about this Journal
Abstract
The empirical Bayes linear loss two-action problem is studied. An empirical Bayes test $\delta$$_{n}$ $^{*}$ is proposed. It is shown that $\delta$$_{n}$ $^{*}$ is asymptotically optimal in the sense that its regret converges to zero at a rate $n^{-1}$ over a class of priors and the rate $n^{-1}$ is the optimal rate of convergence of empirical Bayes tests.sts.
Keywords
Asymptotically optimal; empirical Bayes; minimum regret; optimal rate of convergence;
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