IMPRECISE CONJUGATE PRIOR DENSITIES FOR THE ONE-PARAMETER EXPONENTIAL FAMILY OF DISTRIBUTIONS

被引：9
|
作者：
COOLEN, FPA [1 ]
机构：
[1] EINDHOVEN UNIV TECHNOL,DEPT MATH & COMP SCI,5600 MB EINDHOVEN,NETHERLANDS
来源：
STATISTICS & PROBABILITY LETTERS | 1993年 / 16卷 / 05期
关键词：
BAYESIAN THEORY; IMPRECISE PROBABILITIES; CONJUGATE PRIORS; ONE-PARAMETER EXPONENTIAL FAMILY OF DISTRIBUTIONS;
D O I：
10.1016/0167-7152(93)90066-R
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：
Reconsidering generalizations of the original Bayesian framework that have been suggested during the last three decades, imprecise conjugate prior densities are porposed for members of the one-parameter exponential family of distributions.
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页码：337 / 342
页数：6
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