Global Robustness with Respect to the Loss Function and the Prior
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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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- Global Robustness with Respect to the Loss Function and the Prior
Theory and Decision
Volume 48, Issue 4 , pp 359-381
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- Kluwer Academic Publishers
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- Bayesian Decision Theory
- Global robustness
- Loss function
- Mixture class
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