On Minimaxity and Admissibility of Hierarchical Bayes Estimators

Tatsuya Kubokawa and William E. Strawderman
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Tatsuya Kubokawa: Faculty of Economics, University of Tokyo
William E. Strawderman: Department of Statistics, Rutgers University

No CIRJE-F-308, CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo

Abstract: In the estimation of a mean vector of a multivariate normal distribution, the paper obtains conditions for minimaxity of hierarchical Bayes estimators against hierarchical prior distributions where three types of second stage priors are treated. Conditions for admissibility and inadmissibility of the hierarchical Bayes estimators are also derived by using the same arguments as in Berger and Strawderman (1996). Combining these results yields admissible and minimax hierarchical Bayes estimators.

Pages: 29 pages
Date: 2004-12
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Persistent link: https://EconPapers.repec.org/RePEc:tky:fseres:2004cf308

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