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.


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


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