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
收藏
页码：175 / 186
页数：12
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