Empirical bayes estimation of the mean in a multivariate normal distribution

DOI10.1080/03610928608829244zbMath0631.62064OpenAlexW2110295031MaRDI QIDQ3768195

John E. Rolph, S. James Press

Publication date: 1986

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

Full work available at URL: https://doi.org/10.1080/03610928608829244

zbMATH Keywords

empirical Bayesquadratic lossmultivariate normalprior distributionspositive definitemean vectorhyperparametersprior meanposterior risksintraclass structureJames-Stein- like estimatorsproportionality assumption

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Bayesian problems; characterization of Bayes procedures (62C10) Empirical decision procedures; empirical Bayes procedures (62C12)

Related Items (2)

Superiority of empirical Bayes estimator of the mean vector in multivariate normal distribution ⋮ Probability Integrals of the Multivariate t Distribution

Cites Work

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• A robust generalized Bayes estimator and confidence region for a multivariate normal mean
• Selecting a minimax estimator of a multivariate normal mean
• Families of minimax estimators of the mean of a multivariate normal distribution
• Bayesian Robustness and the Stein Effect
• Data Analysis Using Stein's Estimator and its Generalizations
• Choosing shrinkage estimators for regression problems
• A Simulation Study of Alternatives to Ordinary Least Squares
• Stein's Estimation Rule and Its Competitors--An Empirical Bayes Approach
• Improved Estimators for Coefficients in Linear Regression
• Empirical Bayes on vector observations: An extension of Stein's method

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