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December, 1988 Controlling Risks under Different Loss Functions: The Compromise Decision Problem
Peter J. Kempthorne
Ann. Statist. 16(4): 1594-1608 (December, 1988). DOI: 10.1214/aos/1176351055

Abstract

Controlling Bayes and/or minimax risks under possibly different loss functions is formulated as a problem faced by two or more statisticians who must compromise and agree on the use of a single decision procedure. The theory characterizing solutions to Bayes compromise problems and minimax-Bayes compromise problems is presented. In a Bayes compromise problem, Bayes risks under different prior distributions and/or loss functions are minimized simultaneously. In a minimax-Bayes compromise problem, a Bayes risk under some loss function for a given prior distribution and a maximum risk under a possibly different loss function are minimized simultaneously.

Citation

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Peter J. Kempthorne. "Controlling Risks under Different Loss Functions: The Compromise Decision Problem." Ann. Statist. 16 (4) 1594 - 1608, December, 1988. https://doi.org/10.1214/aos/1176351055

Information

Published: December, 1988
First available in Project Euclid: 12 April 2007

zbMATH: 0666.62008
MathSciNet: MR964940
Digital Object Identifier: 10.1214/aos/1176351055

Subjects:
Primary: 62C05
Secondary: 62C25

Rights: Copyright © 1988 Institute of Mathematical Statistics

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Vol.16 • No. 4 • December, 1988
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