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Titlebook: Statistical Decision Theory and Related Topics V; Shanti S. Gupta,James O. Berger Conference proceedings 1994 Springer Science+Business Me

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Applications and Limitations of Robust Bayesian Bounds and Type II MLEugh examples that include analysis of a paranormal experiment and a hierarchical model. This last example shows a disturbing difference between actual hierarchical Bayesian analysis and robust Bayesian bounds, a difference which also arises if, instead, a Type II MLE or empirical Bayes analysis is performed.
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A Geometric Solution of the Bayesian ,-Optimal Design Problemrix has multiplicity 1 (as in the case of polynomial regression) it is shown that for a sufficiently large number of observations the classical and the Bayesian .-optimal design are supported at the same set of points.
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Loss Functions for Set Estimationverage probability. Such loss functions can suffer from paradoxical behavior of the Bayes rules, and thus may not be appropriate. We investigate the behavior of optimal set estimators for different classes of loss functions and study their decision-theoretic properties.
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