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.
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Abraham, C., Daures, JP. Global Robustness with Respect to the Loss Function and the Prior. Theory and Decision 48, 359–381 (2000). https://doi.org/10.1023/A:1005212125699
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DOI: https://doi.org/10.1023/A:1005212125699