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

Content Provider	Springer Nature Link
Author	Kamińska, Agnieszka
Copyright Year	2008
Abstract	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.
Ending Page	191
Page Count	13
Starting Page	179
File Format	PDF
ISSN	09325026
e-ISSN	16139798
Journal	Statistical Papers
Issue Number	1
Volume Number	51
Language	English
Publisher	Springer-Verlag
Publisher Date	2008-04-02
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Bayes estimation Robustness and adaptive procedures Classes of loss functions Probability Theory and Stochastic Processes Bayesian problems; characterization of Bayes procedures Decision theory Robust Bayes estimation Statistics for Business/Economics/Mathematical Finance/Insurance Point estimation Operations Research/Decision Theory Class of priors Minimax rule Economic Theory
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Statistics, Probability and Uncertainty

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