Statistical Science

Reversing the Stein Effect

Michael D. Perlman and Sanjay Chaudhuri

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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.

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Statist. Sci., Volume 27, Number 1 (2012), 135-143.

First available in Project Euclid: 14 March 2012

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


Perlman, Michael D.; Chaudhuri, Sanjay. Reversing the Stein Effect. Statist. Sci. 27 (2012), no. 1, 135--143. doi:10.1214/09-STS278.

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