On unbiased and improved loss estimation for the mean of a multivariate normal distribution with unknown variance.

DOI10.1016/S0378-3758(02)00406-8zbMath1075.62567MaRDI QIDQ1417791

Alan T. K. Wan, Guo Hua Zou

Publication date: 6 January 2004

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

zbMATH Keywords

RiskJames-Stein estimatorQuadratic lossPositive-part rule

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Admissibility in statistical decision theory (62C15)

Related Items (9)

On improved loss estimation for shrinkage estimators ⋮ Data based loss estimation of the mean of a spherical distribution with a residual vector ⋮ Inadmissibility of the corrected Akaike information criterion ⋮ A note on loss estimation ⋮ Estimates of low bias for the multivariate normal ⋮ Improved loss estimation for a normal mean matrix ⋮ PERFORMANCE LIMITS FOR ESTIMATORS OF THE RISK OR DISTRIBUTION OF SHRINKAGE-TYPE ESTIMATORS, AND SOME GENERAL LOWER RISK-BOUND RESULTS ⋮ A paradoxical argument about domination ⋮ Improved loss estimation for the lasso: a variable selection tool

Cites Work

• Estimation of normal means: Frequentist estimation of loss
• Loss functions for loss estimation
• Admissibility of conditional confidence procedures
• Estimating the loss of estimators of a binomial parameter
• Stein's Estimation Rule and Its Competitors--An Empirical Bayes Approach
• Ancillary Statistics and Estimation of the Loss in Estimation Problems
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