Anna Karenina and the two envelopes problem

IF 0.8 4区 数学 Q3 STATISTICS & PROBABILITY Australian & New Zealand Journal of Statistics Pub Date : 2021-07-21 DOI:10.1111/anzs.12329
R. D. Gill
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引用次数: 1

Abstract

The Anna Karenina principle is named after the opening sentence in the eponymous novel: Happy families are all alike; every unhappy family is unhappy in its own way. The two envelopes problem (TEP) is a much-studied paradox in probability theory, mathematical economics, logic and philosophy. Time and again a new analysis is published in which an author claims finally to explain what actually goes wrong in this paradox. Each author (the present author included) emphasises what is new in their approach and concludes that earlier approaches did not get to the root of the matter. We observe that though a logical argument is only correct if every step is correct, an apparently logical argument which goes astray can be thought of as going astray at different places. This leads to a comparison between the literature on TEP and a successful movie franchise: it generates a succession of sequels, and even prequels, each with a different director who approaches the same basic premise in a personal way. We survey resolutions in the literature with a view to synthesis, correct common errors, and give a new theorem on order properties of an exchangeable pair of random variables, at the heart of most TEP variants and interpretations. A theorem on asymptotic independence between the amount in your envelope and the question whether it is smaller or larger shows that the pathological situation of improper priors or infinite expectation values has consequences as we merely approach such a situation.

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安娜·卡列尼娜和两个信封的问题
安娜·卡列尼娜原则是以同名小说的开头一句话命名的:幸福的家庭都是相似的;不幸的家庭各有各的不幸。双信封问题(TEP)是概率论、数理经济学、逻辑学和哲学中一个被广泛研究的悖论。不断有新的分析发表,其中作者声称最终解释了这个悖论到底出了什么问题。每位作者(包括本作者)都强调了他们方法中的新内容,并得出结论说,以前的方法没有触及问题的根源。我们注意到,虽然逻辑论证只有在每一步都正确的情况下才是正确的,但一个表面上合乎逻辑的论证,如果误入歧途,可以认为是在不同的地方误入歧途。这让我们将TEP的文学作品与成功的电影系列进行比较:它产生了一系列续集,甚至前传,每一部都有不同的导演,以个人的方式处理相同的基本前提。我们调查了文献中的决议,以综合,纠正常见错误,并给出了一个关于可交换随机变量对的阶性质的新定理,这是大多数TEP变体和解释的核心。一个关于你信封里的数量和它是大还是小的问题之间的渐近独立的定理表明,当我们仅仅接近这种情况时,不当先验或无限期望值的病态情况就会产生后果。
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来源期刊
Australian & New Zealand Journal of Statistics
Australian & New Zealand Journal of Statistics 数学-统计学与概率论
CiteScore
1.30
自引率
9.10%
发文量
31
审稿时长
>12 weeks
期刊介绍: The Australian & New Zealand Journal of Statistics is an international journal managed jointly by the Statistical Society of Australia and the New Zealand Statistical Association. Its purpose is to report significant and novel contributions in statistics, ranging across articles on statistical theory, methodology, applications and computing. The journal has a particular focus on statistical techniques that can be readily applied to real-world problems, and on application papers with an Australasian emphasis. Outstanding articles submitted to the journal may be selected as Discussion Papers, to be read at a meeting of either the Statistical Society of Australia or the New Zealand Statistical Association. The main body of the journal is divided into three sections. The Theory and Methods Section publishes papers containing original contributions to the theory and methodology of statistics, econometrics and probability, and seeks papers motivated by a real problem and which demonstrate the proposed theory or methodology in that situation. There is a strong preference for papers motivated by, and illustrated with, real data. The Applications Section publishes papers demonstrating applications of statistical techniques to problems faced by users of statistics in the sciences, government and industry. A particular focus is the application of newly developed statistical methodology to real data and the demonstration of better use of established statistical methodology in an area of application. It seeks to aid teachers of statistics by placing statistical methods in context. The Statistical Computing Section publishes papers containing new algorithms, code snippets, or software descriptions (for open source software only) which enhance the field through the application of computing. Preference is given to papers featuring publically available code and/or data, and to those motivated by statistical methods for practical problems.
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