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.
Publié le : 1988-12-14
Classification:
Bayes inference,
group decision analysis,
minimax,
multiple objective decision analysis,
62C05,
62C25
@article{1176351055,
author = {Kempthorne, Peter J.},
title = {Controlling Risks under Different Loss Functions: The Compromise Decision Problem},
journal = {Ann. Statist.},
volume = {16},
number = {1},
year = {1988},
pages = { 1594-1608},
language = {en},
url = {http://dml.mathdoc.fr/item/1176351055}
}
Kempthorne, Peter J. Controlling Risks under Different Loss Functions: The Compromise Decision Problem. Ann. Statist., Tome 16 (1988) no. 1, pp. 1594-1608. http://gdmltest.u-ga.fr/item/1176351055/