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Confidence sets and the stein effect
Authors:George Casella  Jiunn Tzon Hwang
Affiliation:1. Biometrics Unit , Cornell University , NY, 14853, Ithaca;2. Department of Mathematics , Cornell University , NY, 14853, Ithaca
Abstract:The problem of improving upon the usual set estimator of a multivariate normal mean has only recently seen significant advances. Improved sets that take advantage of the Stein effect have been constructed. It is shown here that the Stein effect is so powerful that one can construct improved confidence sets that can have zero radius on a set of positive probability. Other, somewhat more sensible, sets which attain arbitrarily small radius are also constructed, and it is argued that one way to eliminate unreasonable confidence sets is through a conditional evaluation.
Keywords:multivariate normal mean  stein estimation  empirical bayes  minimax set estimation
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