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Exact and efficient inference for partial Bayes problems. (English) Zbl 1414.62094

This article considers statistical inference for partial Bayes problems, i.e. Bayesian models without fully-specified prior distributions. In these models, the prior information is only partially available. A general inference framework for partial Bayes problems is considered. In addition to the theoretical investigations, numerical results show that the proposed method is superior to the ordinary ones.

MSC:

62F15 Bayesian inference
62F25 Parametric tolerance and confidence regions
62C10 Bayesian problems; characterization of Bayes procedures
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