On the probability of a Pareto record

IF 0.7 3区 工程技术 Q4 ENGINEERING, INDUSTRIAL
James Allen Fill, Ao Sun
{"title":"On the probability of a Pareto record","authors":"James Allen Fill, Ao Sun","doi":"10.1017/s0269964824000081","DOIUrl":null,"url":null,"abstract":"<p>Given a sequence of independent random vectors taking values in <span><span><img data-mimesubtype=\"png\" data-type=\"\" src=\"https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20240603131552515-0032:S0269964824000081:S0269964824000081_inline1.png\"><span data-mathjax-type=\"texmath\"><span>${\\mathbb R}^d$</span></span></img></span></span> and having common continuous distribution function <span>F</span>, say that the <span><span><img data-mimesubtype=\"png\" data-type=\"\" src=\"https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20240603131552515-0032:S0269964824000081:S0269964824000081_inline2.png\"><span data-mathjax-type=\"texmath\"><span>$n^{\\rm \\scriptsize}$</span></span></img></span></span>th observation <span>sets a (Pareto) record</span> if it is not dominated (in every coordinate) by any preceding observation. Let <span><span><img data-mimesubtype=\"png\" data-type=\"\" src=\"https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20240603131552515-0032:S0269964824000081:S0269964824000081_inline3.png\"><span data-mathjax-type=\"texmath\"><span>$p_n(F) \\equiv p_{n, d}(F)$</span></span></img></span></span> denote the probability that the <span><span><img data-mimesubtype=\"png\" data-type=\"\" src=\"https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20240603131552515-0032:S0269964824000081:S0269964824000081_inline4.png\"><span data-mathjax-type=\"texmath\"><span>$n^{\\rm \\scriptsize}$</span></span></img></span></span>th observation sets a record. There are many interesting questions to address concerning <span>p<span>n</span></span> and multivariate records more generally, but this short paper focuses on how <span>p<span>n</span></span> varies with <span>F</span>, particularly if, under <span>F</span>, the coordinates exhibit negative dependence or positive dependence (rather than independence, a more-studied case). We introduce new notions of negative and positive dependence ideally suited for such a study, called <span>negative record-setting probability dependence</span> (NRPD) and <span>positive record-setting probability dependence</span> (PRPD), relate these notions to existing notions of dependence, and for fixed <span><span><img data-mimesubtype=\"png\" data-type=\"\" src=\"https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20240603131552515-0032:S0269964824000081:S0269964824000081_inline5.png\"><span data-mathjax-type=\"texmath\"><span>$d \\geq 2$</span></span></img></span></span> and <span><span><img data-mimesubtype=\"png\" data-type=\"\" src=\"https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20240603131552515-0032:S0269964824000081:S0269964824000081_inline6.png\"><span data-mathjax-type=\"texmath\"><span>$n \\geq 1$</span></span></img></span></span> prove that the image of the mapping <span>p<span>n</span></span> on the domain of NRPD (respectively, PRPD) distributions is <span><span><img data-mimesubtype=\"png\" data-type=\"\" src=\"https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20240603131552515-0032:S0269964824000081:S0269964824000081_inline7.png\"><span data-mathjax-type=\"texmath\"><span>$[p^*_n, 1]$</span></span></img></span></span> (resp., <span><span><img data-mimesubtype=\"png\" data-type=\"\" src=\"https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20240603131552515-0032:S0269964824000081:S0269964824000081_inline8.png\"><span data-mathjax-type=\"texmath\"><span>$[n^{-1}, p^*_n]$</span></span></img></span></span>), where <span><span><img data-mimesubtype=\"png\" data-type=\"\" src=\"https://static.cambridge.org/binary/version/id/urn:cambridge.org:id:binary:20240603131552515-0032:S0269964824000081:S0269964824000081_inline9.png\"><span data-mathjax-type=\"texmath\"><span>$p^*_n$</span></span></img></span></span> is the record-setting probability for any continuous <span>F</span> governing independent coordinates.</p>","PeriodicalId":54582,"journal":{"name":"Probability in the Engineering and Informational Sciences","volume":"35 1","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Probability in the Engineering and Informational Sciences","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1017/s0269964824000081","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0

Abstract

Given a sequence of independent random vectors taking values in Abstract Image${\mathbb R}^d$ and having common continuous distribution function F, say that the Abstract Image$n^{\rm \scriptsize}$th observation sets a (Pareto) record if it is not dominated (in every coordinate) by any preceding observation. Let Abstract Image$p_n(F) \equiv p_{n, d}(F)$ denote the probability that the Abstract Image$n^{\rm \scriptsize}$th observation sets a record. There are many interesting questions to address concerning pn and multivariate records more generally, but this short paper focuses on how pn varies with F, particularly if, under F, the coordinates exhibit negative dependence or positive dependence (rather than independence, a more-studied case). We introduce new notions of negative and positive dependence ideally suited for such a study, called negative record-setting probability dependence (NRPD) and positive record-setting probability dependence (PRPD), relate these notions to existing notions of dependence, and for fixed Abstract Image$d \geq 2$ and Abstract Image$n \geq 1$ prove that the image of the mapping pn on the domain of NRPD (respectively, PRPD) distributions is Abstract Image$[p^*_n, 1]$ (resp., Abstract Image$[n^{-1}, p^*_n]$), where Abstract Image$p^*_n$ is the record-setting probability for any continuous F governing independent coordinates.

关于帕累托记录的概率
给定在 ${mathbb R}^d$ 中取值并具有共同连续分布函数 F 的独立随机向量序列,如果第 $n^{\rm \scriptsize}$ 次观测值(在每个坐标上)不被前面的任何观测值支配,则称该观测值创下了(帕累托)记录。让 $p_n(F) \equiv p_{n, d}(F)$ 表示第 $n^{rm \scriptsize}$ 次观测创下记录的概率。一般来说,关于 pn 和多元记录有许多有趣的问题需要解决,但这篇短文的重点是 pn 如何随 F 变化,特别是如果在 F 下,坐标表现出负依赖性或正依赖性(而不是独立性,这是一种研究较多的情况)。我们引入了非常适合这种研究的新的负依赖性和正依赖性概念,称为负创纪录概率依赖性(NRPD)和正创纪录概率依赖性(PRPD),将这些概念与现有的依赖性概念联系起来,并对固定的 $d \geq 2$ 和 $n \geq 1$ 证明映射 pn 在 NRPD(分别是 PRPD)分布域上的映像是 $[p^*_n, 1]$ (respect、$[n^{-1},p^*_n]$),其中$p^*_n$ 是任何支配独立坐标的连续 F 的创纪录概率。
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来源期刊
CiteScore
2.20
自引率
18.20%
发文量
45
审稿时长
>12 weeks
期刊介绍: The primary focus of the journal is on stochastic modelling in the physical and engineering sciences, with particular emphasis on queueing theory, reliability theory, inventory theory, simulation, mathematical finance and probabilistic networks and graphs. Papers on analytic properties and related disciplines are also considered, as well as more general papers on applied and computational probability, if appropriate. Readers include academics working in statistics, operations research, computer science, engineering, management science and physical sciences as well as industrial practitioners engaged in telecommunications, computer science, financial engineering, operations research and management science.
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