Open Access
February 2012 Reversing the Stein Effect
Michael D. Perlman, Sanjay Chaudhuri
Statist. Sci. 27(1): 135-143 (February 2012). DOI: 10.1214/09-STS278

Abstract

The Reverse Stein Effect is identified and illustrated: A statistician who shrinks his/her data toward a point chosen without reliable knowledge about the underlying value of the parameter to be estimated but based instead upon the observed data will not be protected by the minimax property of shrinkage estimators such as that of James and Stein, but instead will likely incur a greater error than if shrinkage were not used.

Citation

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Michael D. Perlman. Sanjay Chaudhuri. "Reversing the Stein Effect." Statist. Sci. 27 (1) 135 - 143, February 2012. https://doi.org/10.1214/09-STS278

Information

Published: February 2012
First available in Project Euclid: 14 March 2012

zbMATH: 1330.62293
MathSciNet: MR2953500
Digital Object Identifier: 10.1214/09-STS278

Keywords: Bayes and empirical Bayes estimators , James–Stein estimator , multivariate normal distribution , shrinkage estimator

Rights: Copyright © 2012 Institute of Mathematical Statistics

Vol.27 • No. 1 • February 2012
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