Robust Bayesian analysis of the linear regression model

被引：12

作者：

Chaturvedi, A ^{[1
]}

机构：

[1] UNIV ALLAHABAD,DEPT MATH & STAT,ALLAHABAD 211002,UTTAR PRADESH,INDIA

来源：

JOURNAL OF STATISTICAL PLANNING AND INFERENCE | 1996年 / 50卷 / 02期

关键词：

linear regression model; g-priors; Robust Bayes; epsilon-contamination; ML-II;

D O I：

10.1016/0378-3758(95)00052-6

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：

The robust Bayesian analysis of the linear regression model is presented under the assumption of a mixture of g-prior distributions for the parameters and ML-II posterior density for the coefficient vector is derived. Robustness properties of the ML-II posterior mean are studied. Utilizing the ML-II posterior density, robust Bayes predictors for the future values of the dependent variable are also obtained.

引用

页码：175 / 186

页数：12

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