Global Robustness with Respect to the Loss Function and the Prior |
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Authors: | Abraham Christophe Daures Jean-Pierre |
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Affiliation: | (1) Unité de Biométrie, ENSA.M INRA, 2, Place P. Viala, 34060 Montpellier cedex 1, France |
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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 , we obtain the exact set. |
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Keywords: | Bayesian Decision Theory Global robustness Loss function Mixture class |
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