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On Minimaxity and Admissibility of Hierarchical Bayes Estimators


  • Tatsuya Kubokawa

    (Faculty of Economics, University of Tokyo)

  • William E. Strawderman

    (Department of Statistics, Rutgers University)


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.

Suggested Citation

  • Tatsuya Kubokawa & William E. Strawderman, 2004. "On Minimaxity and Admissibility of Hierarchical Bayes Estimators," CIRJE F-Series CIRJE-F-308, CIRJE, Faculty of Economics, University of Tokyo.
  • Handle: RePEc:tky:fseres:2004cf308

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