COHERENT STATISTICAL-INFERENCE AND BAYES THEOREM
成果类型：
Article
署名作者：
BERTI, P; REGAZZINI, E; RIGO, P
署名单位：
Bocconi University; University of Florence
刊物名称：
ANNALS OF STATISTICS
ISSN/ISSBN：
0090-5364
DOI：
10.1214/aos/1176347988
发表日期：
1991
页码：
366-381
关键词：
摘要：
Conditions are given which suffice for the assessment of a coherent inference by means of a Bayesian algorithm, i.e., a suitable extension of the classical Bayes theorem relative to a finite number of alternatives. Under some further hypotheses such inference is shown to be, in addition, coherent in the sense of Heath, Lane and Sudderth. Moreover, a characterization of coherent posteriors is provided, together with some remarks concerning finitely additive conditional probabilities.