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Linear Bayes and minimax estimation in linear models with partially restricted parameter space. (English) Zbl 0780.62027
Summary: Linear minimax estimation in linear models with partial parameter restrictions can be reduced to a minimax estimation problem under full parameter restrictions. This is due to the duality between minimax and Bayes estimation w.r.t. least favourable prior distributions, and to a decomposition result for Bayes estimators. As an application we find some new results for minimax estimators under partial parameter restrictions.

MSC:
62F15 Bayesian inference
62C20 Minimax procedures in statistical decision theory
62F30 Parametric inference under constraints
62F10 Point estimation
62J05 Linear regression; mixed models
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