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On Minimaxity and Admissibility of Hierarchical Bayes Estimators

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  • Tatsuya Kubokawa

    (Faculty of Economics, University of Tokyo)

  • William E. Strawderman

    (Department of Statistics, Rutgers University)

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    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.

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    Bibliographic Info

    Paper provided by CIRJE, Faculty of Economics, University of Tokyo in its series CIRJE F-Series with number CIRJE-F-308.

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    Length: 29 pages
    Date of creation: Dec 2004
    Date of revision:
    Handle: RePEc:tky:fseres:2004cf308

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