Minimax estimation of a multivariate normal mean under arbitrary quadratic loss

James Berger

Journal of Multivariate Analysis, 1976, vol. 6, issue 2, 256-264

Abstract: Let X be a p-variate (p >= 3) vector normally distributed with mean [theta] and known covariance matrix . It is desired to estimate [theta] under the quadratic loss ([delta] - [theta])t Q([delta] - [theta]), where Q is a known positive definite matrix. A broad class of minimax estimators for [theta] is developed.

Keywords: Multivariate; normal; distribution; quadratic; loss; risk; function; minimax; estimator (search for similar items in EconPapers)
Date: 1976
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Citations: View citations in EconPapers (3)

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