Universal estimators of a vector parameter

A. L. Rukhin

Journal of Multivariate Analysis, 1984, vol. 14, issue 2, 135-154

Abstract: Let x be a random sample with a distribution depending on a vector parameter [theta] [set membership, variant] m. The description of distributions and generalized prior densities on m is given, for which the generalized Bayes estimator of [theta], based on x, is the same for all symmetric loss functions. These distributions form a special subclass of exponential family. The specification of this result for the case of a location parameter is considered. The proof of the main theorem is based on the solution of a functional equation of D'Alembert's type.

Keywords: generalized; Bayes; estimators; CS; set; of; loss; functions; universal; estimators; exponential; family; functional; equation; of; the; D'Alembert's; type (search for similar items in EconPapers)
Date: 1984
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