James-stein estimation with constraints on the norm

DOI10.1080/03610929308831192zbMath0797.62043OpenAlexW2009678139MaRDI QIDQ4275851

N. C. Giri, Éric Marchand

Publication date: 27 October 1994

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610929308831192

zbMATH Keywords

quadratic lossminimal complete classoptimal decision ruleJames-Stein type decision rulesmultivariant meansample mean dominationvariance mixture of normals

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Complete class results in statistical decision theory (62C07)

Related Items (3)

Estimation of the mean of a spherically symmetric distribution with constraints on the norm ⋮ Estimation of a parameter vector when some components are restricted ⋮ On the inevitability of a paradox in shrinkage estimation for scale mixtures of normals.

Cites Work

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• Equivariant estimation in a model with an ancillary statistic
• A note on adaptive generalized ridge regression estimator
• The geometry of exponential families
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• On the best equivariant estimator of mean of a multivariate normal population
• Differential geometry of curved exponential families. Curvatures and information loss
• Minimax estimation of location parameters for certain spherically symmetric distributions
• Improved shrinkage estimators for the mean vector of a scale mixture of normals with unknown variance
• An explicit formula for the risk of James-Stein estimators
• Conditional inference about a normal mean with known coefficient of variation

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