Efficiency of Linear Bayes Rules for a Normal Mean: Skewed Priors Class Academic Article

abstract

• [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.]

authors

• Vidakovic, Brani

published proceedings

• Journal of the Royal Statistical Society Series D (The Statistician)

author list (cited authors)

• Mukhopadhyay, S., & Vidakovic, B.

citation count

• 16

complete list of authors

• Mukhopadhyay, Saurabh||Vidakovic, Brani

publication date

• January 1995

publisher

• JSTOR  Publisher

published in

• Journal of the Royal Statistical Society Series D (The Statistician)  Journal

Digital Object Identifier (DOI)

• 10.2307/2348710

start page

• 389

end page

• 397

volume

• 44

issue

• 3

URL

• http://dx.doi.org/10.2307/2348710