The equivalence of Bayes and robust Bayes estimators for various loss functions

被引：0
|
作者：
Agnieszka Kamińska
机构：
[1] Wrocław University of Technology,Institute of Mathematics and Computer Science
来源：
Statistical Papers | 2010年 / 51卷
关键词：
Decision theory; Bayes estimation; Class of priors; Robust Bayes estimation; Minimax rule; Classes of loss functions; 62C10; 62F35; 62F10;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The problem of Bayes and robust Bayes estimation for various bounded and/or symmetric loss functions in a normal model with conjugate and non-informative prior distributions is considered. The prior distribution is not fully specified and covers the conjugate family of priors. It is of interest to know that the Bayes and robust Bayes estimators for symmetric losses are the same as those for the standard square-error loss function.
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页码：179 / 191
页数：12
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