THE FORMAL DEFINITION OF REFERENCE PRIORS

被引:271
作者
Berger, James O. [1 ]
Bernardo, Jose M. [2 ]
Sun, Dongchu [3 ]
机构
[1] Duke Univ, Dept Stat Sci, Durham, NC 27708 USA
[2] Fac Math, Dept Estadist, Valencia 46100, Spain
[3] Univ Missouri, Dept Stat, Columbia, MO 65211 USA
基金
美国国家科学基金会;
关键词
Amount of information; Bayesian asymptotics; consensus priors; Fisher information; Jeffreys priors; noninformative priors; objective priors; reference priors; BAYESIAN-ANALYSIS; POSTERIOR; DISTRIBUTIONS; PROBABILITY; INFORMATION; CONVERGENCE; INFERENCE;
D O I
10.1214/07-AOS587
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
Reference analysis produces objective Bayesian inference, in the sense that inferential statements depend only on the assumed model and the available data, and the prior distribution used to make an inference is least informative in a certain information-theoretic sense. Reference priors have been rigorously defined in specific contexts and heuristically defined in general, but a rigorous general definition has been lacking. We produce a rigorous general definition here and then show how an explicit expression for the reference prior can be obtained under very weak regularity conditions. The explicit expression can be used to derive new reference priors both analytically and numerically.
引用
收藏
页码:905 / 938
页数:34
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