On Minimaxity and Admissibility of Hierarchical Bayes Estimators
AbstractIn 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.
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Bibliographic InfoPaper provided by CIRJE, Faculty of Economics, University of Tokyo in its series CIRJE F-Series with number CIRJE-F-308.
Length: 29 pages
Date of creation: Dec 2004
Date of revision:
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-12-12 (All new papers)
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