The Dempster-Shafer calculus for statisticians

被引:246
作者
Dempster, A. P. [1 ]
机构
[1] Harvard Univ, Dept Stat, Cambridge, MA 02138 USA
关键词
Dempster-Shafer; belief functions; state space; Poisson model; join-tree computation; statistical significance; dull null hypothesis;
D O I
10.1016/j.ijar.2007.03.004
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The Dempster-Shafer (E)S) theory of probabilistic reasoning is presented in terms of a semantics whereby every meaningful formal assertion is associated with a triple (p, q, r) where p is the probability "for" the assertion, q is the probability "against" the assertion, and r is the probability of "don't know". Arguments are presented for the necessity of "don't know". Elements of the calculus are sketched, including the extension of a DS model from a margin to a full state space, and DS combination of independent DS uncertainty assessments on the full space. The methodology is applied to inference and prediction from Poisson counts, including an introduction to the use of join-tree model structure to simplify and shorten computation. The relation of DS theory to statistical significance testing is elaborated, introducing along the way the new concept of "dull" null hypothesis. (C) 2007 Elsevier Inc. All rights reserved.
引用
收藏
页码:365 / 377
页数:13
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