On Minimaxity and Admissibility of Hierarchical Bayes Estimators
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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|Date of creation:||Dec 2004|
|Date of revision:|
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