信心即可能性

IF 3.9 1区 数学 Q1 STATISTICS & PROBABILITY Statistical Science Pub Date : 2021-01-01 DOI:10.1214/20-sts811
Y. Pawitan, Youngjo Lee
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引用次数: 9

摘要

置信度和似然度是具有不同技术解释和用法的基本统计概念。在置信区间过程中,置信度是一个有意义的不确定性概念,而似然主要被用作统计建模和给定观测数据推断的工具。在这里,我们表明信心实际上是一种扩展的可能性,从而在两个概念之间给出了更紧密的对应关系。这一结果使置信概念在置信区间上下文之外具有外部意义,反之亦然,它为似然提供了置信解释。除了明显的解释目的之外,这种联系表明技术信息的双向转移。例如,扩展似然理论提供了一种更新或组合置信度信息的清晰方法。另一方面,置信度连接使扩展似然直接获得频率概率,这是经典似然无法直接获得的客观证明。这意味着由扩展似然导出的区间与置信区间具有相同的逻辑状态,从而简化了随机参数推理中的术语。
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Confidence as Likelihood
Confidence and likelihood are fundamental statistical concepts with distinct technical interpretation and usage. Confidence is a meaningful concept of uncertainty within the context of confidence-interval procedure, while likelihood has been used predominantly as a tool for statistical modelling and inference given observed data. Here we show that confidence is in fact an extended likelihood, thus giving a much closer correspondence between the two concepts. This result gives the confidence concept an external meaning outside the confidence-interval context, and vice versa, it gives the confidence interpretation to the likelihood. In addition to the obvious interpretation purposes, this connection suggests two-way transfers of technical information. For example, the extended likelihood theory gives a clear way to update or combine confidence information. On the other hand, the confidence connection gives the extended likelihood direct access to the frequentist probability, an objective certification not directly available to the classical likelihood. This implies that intervals derived from the extended likelihood have the same logical status as confidence intervals, thus simplifying the terminology in the inference of random parameters.
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来源期刊
Statistical Science
Statistical Science 数学-统计学与概率论
CiteScore
6.50
自引率
1.80%
发文量
40
审稿时长
>12 weeks
期刊介绍: The central purpose of Statistical Science is to convey the richness, breadth and unity of the field by presenting the full range of contemporary statistical thought at a moderate technical level, accessible to the wide community of practitioners, researchers and students of statistics and probability.
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