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A formal bayes multiple shrinkage estimator
Authors:Edward I. George
Affiliation:Graduate School of Business , University of Chicago , Chicago, 60637, Illinois
Abstract:A new minimax multiple shrinkage estimator is constructed. This estimator which can adaptively shrink towards many subspace targets, is formal Bayes with respect to a mixture of harmonic priors. Unbiased estimates of risk and simulation results suggest that the risk properties of this estimator are very similar to those of the multiple shrinkage Stein estimator proposed by George (1986a). A special case is seen to be admissible.
Keywords:minimax  multivariate normal mean  superharmonic function  stein estimatiom  unbaised estimate of risk
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