Eliciting vague but proper maximal entropy priors in Bayesian experiments
Eliciting vague but proper maximal entropy priors in Bayesian experiments
复制标题
在贝叶斯实验中引出模糊但适当的最大熵先验
DOI：
10.1007/s00362-008-0149-9
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发表时间：
2010
影响因子：
1.3
通讯作者：
N. Bousquet
中科院分区：
文献类型：
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作者：
N. Bousquet
根据最大熵规则得到的先验信息已经在客观和主观贝叶斯分析中使用了多年。然而，当先验知识仍然模糊或可疑时，它们经常遭受不适当的使用，这可能使它们不舒服。在这篇文章中，我们建议的标准最大熵（ME）先验和最大数据信息（MDI）先验，这可以导致获得适当的家庭的一个包含家庭的正式启发。在信道编码的目标框架中给出了解释。在一个主观的框架中，该方法的性能显示在一个可靠性的上下文中时，平坦的，但适当的先验引起的威布尔寿命分布。这样的先验知识似乎是敏感性研究的实用工具。
Priors elicited according to maximal entropy rules have been used for years in objective and subjective Bayesian analysis. However, when the prior knowledge remains fuzzy or dubious, they often suffer from impropriety which can make them uncomfortable to use. In this article we suggest the formal elicitation of an encompassing family for the standard maximal entropy (ME) priors and the maximal data information (MDI) priors, which can lead to obtain proper families. An interpretation is given in the objective framework of channel coding. In a subjective framework, the performance of the method is shown in a reliability context when flat but proper priors are elicited for the Weibull lifetime distributions. Such priors appear as practical tools for sensitivity studies.