Robust Bayesian estimator in a normal model with uncertain hierarchical priors

被引：0

作者：

Hu, Guikai ^{[1
]}

Xiao, Xinhai ^{[1
]}

机构：

[1] East China Univ Technol, Sch Sci, Nanchang 330013, Jiangxi, Peoples R China

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2023年 / 52卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Robust Bayes estimator; uncertainty hierarchical priors; error variance; normal linear model;

D O I：

10.1080/03610926.2021.1917615

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this paper, robust Bayesian estimators of error variance in a normal linear model with uncertain hierarchical prior information are investigated. The posterior regret gamma minimax estimator, the least sensitive estimator and conditional gamma minimax estimator for error variance are obtained under two different classes of priors, respectively. A simulation study is used to compare the performance of the proposed estimators. A real data example is also given to illustrate the results.

引用

页码：567 / 582

页数：16

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