Group-Linear Empirical Bayes Estimates for a Heteroscedastic Normal Mean

DOI10.1080/01621459.2017.1280406zbMath1398.62067arXiv1503.08503OpenAlexW779680562MaRDI QIDQ4962437

Zhuang Ma, Asaf Weinstein, Cun-Hui Zhang, Lawrence D. Brown

Publication date: 2 November 2018

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1503.08503

zbMATH Keywords

empirical Bayesheteroscedasticityshrinkage estimatorasymptotic optimalitycompound decision

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Point estimation (62F10) Bayesian inference (62F15) Analysis of variance and covariance (ANOVA) (62J10) Empirical decision procedures; empirical Bayes procedures (62C12)

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Uses Software

• mixfdr

Cites Work

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• The data-smoothing aspect of Stein estimates
• An empirical Bayes mixture method for effect size and false discovery rate estimation
• A robust generalized Bayes estimator and confidence region for a multivariate normal mean
• Selecting a minimax estimator of a multivariate normal mean
• Minimax estimators of the mean of a multivariate normal distribution
• Admissible minimax estimation of a multivariate normal mean with arbitrary quadratic loss
• Adaptive wavelet estimation: A block thresholding and oracle inequality approach
• Improved minimax estimation of a multivariate normal mean under heteroscedasticity
• General maximum likelihood empirical Bayes estimation of normal means
• Nonparametric empirical Bayes and compound decision approaches to estimation of a high-dimensional vector of normal means
• In-season prediction of batting averages: a field test of empirical Bayes and Bayes methodol\-ogies
• Estimation with Incompletely Specified Loss Functions (the Case of Several Location Parameters)
• SURE Estimates for a Heteroscedastic Hierarchical Model
• Stein's Estimation Rule and Its Competitors--An Empirical Bayes Approach
• Steinized Empirical Bayes Estimation for Heteroscedastic Data