Nonparametric Bayesian robustness

被引：0
|
作者：
Ruggeri, Fabrizio [1 ]
机构：
[1] CNR IMATI, Via Bassini 15, I-20133 Milan, Italy
来源：
CHILEAN JOURNAL OF STATISTICS | 2010年 / 1卷 / 02期
关键词：
Bayesian robustness; Concentration function; Dirichlet process;
D O I：
暂无
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：
A new, nonparametric, approach to Bayesian robustness is presented. Whereas many studies in Bayesian robustness have dealt with a parametric sampling distribution, considering classes of prior distributions on the parameters, here we assume that the sampling distribution comes from a Dirichlet process with a parameter eta = beta alpha, with beta > 0 and alpha being a probability measure, specified with uncertainty.
引用
收藏
页码：51 / 68
页数：18
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