Admissible linear estimators of the multivariate normal mean without extra information

DOI10.1007/BF02925488zbMath0719.62017MaRDI QIDQ5751744

Liqun Wang

Publication date: 1991

Published in: Statistical Papers (Search for Journal in Brave)

zbMATH Keywords

normal linear modelquadratic lossmultivariate normal meanlinear estimatorStein-type estimatorsunknown covariance

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Admissibility in statistical decision theory (62C15)

Cites Work

• Unnamed Item
• Unnamed Item
• Admissible linear estimators in the general Gauss-Markov model
• On the structure of admissible linear estimators
• Admissibility in linear estimation
• Admissible minimax estimation of a multivariate normal mean with arbitrary quadratic loss
• Estimation of parameters in a linear model
• Admissible linear estimation in singular linear models
• PRINCIPAL COMPONENTS AND THE PROBLEM OF MULTICOLLINEARITY(*)
• All Admissible Linear Estimates of the Mean Vector
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• On Biased Estimation in Linear Models

This page was built for publication: Admissible linear estimators of the multivariate normal mean without extra information