Applications of Improved Variance Estimators in a Multivariate Normal Mean Vector Estimation

DOI10.1080/02331889708802604zbMath0915.62048OpenAlexW1981774116MaRDI QIDQ4375880

Ching-Hui Chang, Nabendu Pal, Jyh-Jiuan Lin

Publication date: 8 February 1998

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331889708802604

zbMATH Keywords

shrinkage estimationloss functionrisk function

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Point estimation (62F10) Admissibility in statistical decision theory (62C15)

Related Items (1)

Stein estimation -- a review

Cites Work

• An approach to improving the James-Stein estimator
• Estimation of the mean of a multivariate normal distribution
• A sequence of improvements over the James-Stein estimator
• Minimax estimation of powers of the variance of a normal population under squared error loss
• A unified approach to improving equivariant estimators
• Improving the James-Stein estimator using the Stein variance estimator
• Improving on equivariant estimators
• Estimation of the variance and its applications
• Inadmissibility of the usual estimator for the variance of a normal distribution with unknown mean
• Inadmissibility of the Usual Estimators of Scale parameters in Problems with Unknown Location and Scale Parameters

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