Minimaxity of empirical bayes estimators of the means of independent normal variables with unequal variances

DOI10.1080/03610929308831140zbMath0785.62006OpenAlexW2049292345MaRDI QIDQ4275816

Nobuo Shinozaki, Yuan-Tsung Chang

Publication date: 31 January 1994

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

Full work available at URL: https://doi.org/10.1080/03610929308831140

zbMATH Keywords

squared error loss functionrisk behaviorcommon priorStein estimatoruniform improvementempirical Bayes estimatorssimultaneous estimation of normal meansmaximum likelihood approachMonte Carlo simulation resultsweighted sum of squared error loss

Mathematics Subject Classification ID

Minimax procedures in statistical decision theory (62C20) Empirical decision procedures; empirical Bayes procedures (62C12)

Related Items (6)

Improved Empirical Bayes Ridge Regression Estimators Under Multicollinearity ⋮ Minimaxity of empirical bayes estimators shrinking toward the grand mean when variances are unequal ⋮ Empirical Bayes regression analysis with many regressors but fewer observations ⋮ Dominance properties of constrained Bayes and empirical Bayes estimators ⋮ Shrinkage estimation with singular priors and an application to small area estimation ⋮ Minimax Empirical Bayes Estimators in Multivariate Mixed Linear Models with Unequal Replications

Cites Work

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• Statistical decision theory and Bayesian analysis. 2nd ed
• Estimation of the mean of a multivariate normal distribution
• Minimax estimators of the mean of a multivariate normal distribution
• Admissible minimax estimation of a multivariate normal mean with arbitrary quadratic loss
• Minimax estimation of a multivariate normal mean under polynomial loss
• Stein estimation: The spherically symmetric case
• Subjective hierarchical Bayes estimation of a multivariate normal mean: On the frequentist interface
• Estimating the Mean of a Multivariate Normal Population with General Quadratic Loss Function

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