Generalized Bayes minimax estimation of the normal mean matrix with unknown covariance matrix

Hisayuki Tsukuma

Journal of Multivariate Analysis, 2009, vol. 100, issue 10, 2296-2304

Abstract: This paper addresses the problem of estimating the normal mean matrix in the case of unknown covariance matrix. This problem is solved by considering generalized Bayesian hierarchical models. The resulting generalized Bayes estimators with respect to an invariant quadratic loss function are shown to be matricial shrinkage equivariant estimators and the conditions for their minimaxity are given.

Keywords: Decision; theory; Equivariance; Generalized; Bayes; estimation; Hierarchical; model; Minimaxity; Multivariate; linear; model; Posterior; mean; Quadratic; loss; Shrinkage; estimator (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (7)

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