Theory and Decision

, Volume 48, Issue 4, pp 359–381

Global Robustness with Respect to the Loss Function and the Prior

  • Christophe Abraham
  • Jean-Pierre Daures
Article

DOI: 10.1023/A:1005212125699

Cite this article as:
Abraham, C. & Daures, JP. Theory and Decision (2000) 48: 359. doi:10.1023/A:1005212125699

Abstract

We propose a class [I,S] of loss functions for modeling the imprecise preferences of the decision maker in Bayesian Decision Theory. This class is built upon two extreme loss functions I and S which reflect the limited information about the loss function. We give an approximation of the set of Bayes actions for every loss function in [I,S] and every prior in a mixture class; if the decision space is a subset of ℝ, we obtain the exact set.

Bayesian Decision TheoryGlobal robustnessLoss functionMixture class

Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  • Christophe Abraham
    • 1
  • Jean-Pierre Daures
    • 1
  1. 1.Unité de BiométrieENSA.M INRAMontpellier cedex 1France