Efficiency of Linear Bayes Rules for a Normal Mean: Skewed Priors Class
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[In this paper we explore the performance of linear Bayes rules in estimating a normal mean. We take a robust Bayesian standpoint, expressing our limited information about the parameter by adopting a family $Gamma$ of priors. The family of priors that we are using is fully described by Azzalini and is suitable for modelling non-symmetric situations. We find in many cases that the linear Bayes rules have reasonably high efficiencies (with respect to the corresponding Bayes rules) and therefore can be used instead of the Bayes rules as the linear rules are much easier to obtain.]
author list (cited authors)
Mukhopadhyay, S., & Vidakovic, B.
complete list of authors
Mukhopadhyay, Saurabh||Vidakovic, Brani