Eliciting Informative Priors by Modeling Expert Decision Making

IF 2.5 4区 管理学 Q3 MANAGEMENT Decision Analysis Pub Date : 2023-09-15 DOI:10.1287/deca.2023.0046
Julia R. Falconer, Eibe Frank, Devon L. L. Polaschek, Chaitanya Joshi
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Abstract

There are significant limitations to current methods for eliciting the prior beliefs of experts. To combat some of these limitations, this paper proposes an alternative approach that infers an expert’s prior beliefs about an uncertain event, A, from the expert’s past decisions. We show that an analyst can use past information on an expert’s decision-making task, contingent on an expert’s prior of A, to model the decision-making process and infer an approximation of the prior for A. This concept is illustrated by an application to recidivism. We conclude this work by highlighting important directions for future research. Funding: J. R. Falconer’s research is funded through the University of Waikato Doctoral Scholarship.
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通过建模专家决策来获取信息先验
目前用于引出专家的先验信念的方法有很大的局限性。为了克服这些限制,本文提出了一种替代方法,即从专家过去的决策中推断专家对不确定事件A的先验信念。我们表明,分析师可以利用专家决策任务的过去信息,根据专家对A的先验,对决策过程进行建模,并推断出A的先验近似值。最后,我们强调了未来研究的重要方向。资助:j.r. Falconer的研究由怀卡托大学博士奖学金资助。
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来源期刊
Decision Analysis
Decision Analysis MANAGEMENT-
CiteScore
3.10
自引率
21.10%
发文量
19
期刊最新文献
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