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本页整理公开书目信息,不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成,未完成全文核验,可能有误;具体假设、证明与结论请核对原文。摘要保留来源文本,未经模型改写。

DOI 首次登记不等于接收或发表日期。部分更正、评论等条目没有独立摘要;缺少可靠材料时保留待补状态。

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分类依据与纠错

AI 根据所提供的论文材料归类:材料聚焦贝叶斯检验基础与方法评论,未明确涉及所列经济计量细分方向。

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代码、数据与补充材料

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关注这篇论文的作者
Christian P Robert
Joshua Bon

Robert 与 Bon 对《安全检验》的讨论意见

研究问题
这篇讨论关注 e 值与 Bayes 因子的联系能否帮助构造最不利先验和参考检验,以及与序贯模型选择是否存在联系。
方法与思路
讨论作者评议主论文中的先验构造、干扰参数的不适当先验处理,并提出反向先验选择和序贯 Monte Carlo 的可能研究方向。
材料陈述的贡献
所给材料提出对贝叶斯基础的解释与若干开放问题;讨论作者对该方案能否导出有用的参考检验程序仍持保留判断。
阅读关注点
应区分主论文定理与讨论作者的评价,核对 e 值和 Bayes 因子的联系所需条件,以及序贯模型选择建议是否已有证明。
阅读边界
材料是版本未注明的 OpenAlex 索引讨论文本,并非《安全检验》主论文摘要;提及的定理属于被讨论论文,开放问题不能当作已获结果。

原文摘要

Central to our interest in Bayesian foundations and reference priors, the connection made in this paper between e-values and Bayes factors, despite the cautionary added label of an ‘Almost Bayesian Case’, could bring a formal way to define least favourable priors (Berger, 1985) in a testing environment, albeit in no clear connection with the reference priors of Bayarri and Garcia-Donato (2007). This derivation, formalized as Theorem 1, provides a reversal of the typical prior choice in testing. A more common stance is to hold the (subjectively chosen) prior distribution on H0 as a starting point—this is an obviously known entity. One may wonder if a dual perspective, i.e. when starting from the prior distribution on H0⁠, would prove fruitful, e.g. in leading to an optimal prior on H1⁠. As a plus, however, the approach found therein allows for improper priors on the nuisance parameters and thus somehow brings a stronger justification than (Berger et al., 1998) in favour of the permanence of an identical measure (on the nuisance parameters) across hypotheses and models. Regarding the sequential directions of the paper, we wonder at its potential connections with sequential Monte Carlo, for instance, towards conducting sequential model choice by constructing efficiently an amalgamated evidence value when the product of Bayes factors is not a Bayes factor (see, e.g. Buchholz et al., 2023). In conclusion, we congratulate the authors on this worthwhile endeavour but remain agnostic as to whether or not the proposal may prove fruitful in the derivation of reference testing procedures. Funded by the European Union (ERC-2022-SYG-OCEAN-101071601) and by a Prairie chair from the Agence Nationale de la Recherche (ANR-19-P3IA-0001). Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the Agence Nationale de la Recherche, the European Union, or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.

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