HIERARCHICAL BAYES ESTIMATORS OF THE ERROR VARIANCE IN ONE-WAY ANOVA MODELS

被引：9

作者：

DATTA, GS

GHOSH, M

机构：

[1] UNIV GEORGIA,FRANKLIN COLL ARTS & SCI,DEPT STAT,ATHENS,GA 30602

[2] UNIV FLORIDA,DEPT STAT,GAINESVILLE,FL 32611

来源：

JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 1995年 / 45卷 / 03期

基金：

美国国家科学基金会;

关键词：

ERROR VARIANCE; ANOVA; HIERARCHICAL BAYES; MINIMAX; PROBABILITY MATCHING CRITERION;

D O I：

10.1016/0378-3758(93)00083-T

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：

For estimating the error variance in the one-way ANOVA problem, the paper proposes a class of hierarchical Bayes (HE) estimators which overcomes the Neyman-Scott problem. A subclass of these HB estimators is found to be minimax. The resulting class of priors is strictly contained within the class of HB priors which meets Peers's criterion of matching asymptotically the posterior probability of a credible set and the frequentist probability up to a certain order.

引用

页码：399 / 411

页数：13

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