Uniform priors on convex sets improve risk

J. A. Hartigan

Statistics & Probability Letters, 2004, vol. 67, issue 4, 285-288

Abstract: Let X be spherical normal with mean [theta] lying in a closed convex set C with a non-empty interior and a non-empty complement. For the prior distribution uniform over C, the mean squared error risk of the generalized Bayes estimator is less than or equal to that of X for [theta][set membership, variant]C. It is equal to that of X if and only if C is a cone, and [theta] is an apex of the cone.

Keywords: Uniform; priors; Bayes; estimators; Squared; error; loss; Improving; risk; Convex; sets; Multivariate; normal (search for similar items in EconPapers)
Date: 2004
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Citations: View citations in EconPapers (14)

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