On the inevitability of a paradox in shrinkage estimation for scale mixtures of normals.

DOI10.1016/S0378-3758(03)00109-5zbMath1044.62060MaRDI QIDQ1427796

Dominique Fourdrinier, William E. Strawderman, Éric Marchand

Publication date: 14 March 2004

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

zbMATH Keywords

Laplace transformsShrinkage estimationLocation parameterQuadratic lossScale mixtures of normals

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Point estimation (62F10) Minimax procedures in statistical decision theory (62C20) Statistical decision theory (62C99) Admissibility in statistical decision theory (62C15)

Cites Work

• Robust shrinkage estimators of the location parameter for elliptically symmetric distributions
• A paradox concerning shrinkage estimators: Should a known scale parameter be replaced by an estimated value in the shrinkage factor?
• Minimax ridge regression estimation
• Minimax estimators of the mean of a multivariate normal distribution
• Shrinkage estimators under spherical symmetry for the general linear model
• An explicit formula for the risk of James-Stein estimators
• James-stein estimation with constraints on the norm

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