On minimaxity and admissibility of hierarchical Bayes estimators

Tatsuya Kubokawa and William E. Strawderman

Journal of Multivariate Analysis, 2007, vol. 98, issue 4, 829-851

Abstract: This paper obtains conditions for minimaxity of hierarchical Bayes estimators in the estimation of a mean vector of a multivariate normal distribution. Hierarchical prior distributions with three types of second stage priors are treated. Conditions for admissibility and inadmissibility of the hierarchical Bayes estimators are also derived using the arguments in Berger and Strawderman [Choice of hierarchical priors: admissibility in estimation of normal means, Ann. Statist. 24 (1996) 931-951]. Combining these results yields admissible and minimax hierarchical Bayes estimators.

Keywords: Admissibility; Bayes; inference; Estimation; Hierarchical; Bayes; model; Inadmissibility; Minimaxity; Mixed; linear; model; Multivariate; normal; distribution; Shrinkage; estimation (search for similar items in EconPapers)
Date: 2007
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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