Empirical Bayes and Selective Inference

被引：0

作者：

Rasines, Daniel Garcia ^{[1
]}

Young, G. Alastair ^{[2
]}

机构：

[1] CSIC, Inst Ciencias Matemat, Madrid, Spain

[2] Imperial Coll London, Dept Math, London, England

来源：

JOURNAL OF THE INDIAN INSTITUTE OF SCIENCE | 2022年 / 102卷 / 04期

关键词：

Empirical Bayes; James-Stein estimator; Normal means problem; Randomisation; Selective inference; Shrinkage;

D O I：

10.1007/s41745-022-00286-0

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

We review the empirical Bayes approach to large-scale inference. In the context of the problem of inference for a high-dimensional normal mean, empirical Bayes methods are advocated as they exhibit risk-reducing shrinkage, while establishing appropriate control of frequentist properties of the inference. We elucidate these frequentist properties and evaluate the protection that empirical Bayes provides against selection bias.

引用

页码：1205 / 1217

页数：13

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