BELIEF FUNCTIONS AND STATISTICAL-INFERENCE

被引：51

作者：

WASSERMAN, LA ^{[1
]}

机构：

[1] CARNEGIE MELLON UNIV,DEPT STAT,PITTSBURGH,PA 15213

来源：

CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE | 1990年 / 18卷 / 03期

关键词：

Belief functions; Choquet capacities; posterior bounds; robust Bayesian inference; upper and lower probabilities;

D O I：

10.2307/3315449

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 Dempster Shafer theory of belief functions is a method of quantifying uncertainty that generalizes probability theory. We review the theory of belief functions in the context of statistical inference. We mainly focus on a particular belief function based on the likelihood function and its application to problems with partial prior information. We also consider connections to upper and lower probabilities and Bayesian robustness. Copyright © 1990 Statistical Society of Canada

引用

页码：183 / 196

页数：14

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