基于负荷分担模型的聚合悖论构建

IF 0.9 4区数学 Q3 STATISTICS & PROBABILITY Advances in Applied Probability Pub Date : 2022-08-08 DOI:10.1017/apr.2022.17

Emilio De Santis, F. Spizzichino

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引用次数: 2

摘要

摘要我们证明了负载分担模型（一类非常特殊的非负随机变量的多变量概率模型）可以用于获得关于随机优先级的多变量扩展和相关悖论的基本结果。这样的结果可以应用于几个不同的领域。特别是，它们的应用可以在投票理论中出现的悖论的背景下发展。此外，在系统可靠性领域中，应用概率签名的概念可能是令人感兴趣的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Construction of aggregation paradoxes through load-sharing models

Abstract We show that load-sharing models (a very special class of multivariate probability models for nonnegative random variables) can be used to obtain basic results about a multivariate extension of stochastic precedence and related paradoxes. Such results can be applied in several different fields. In particular, applications of them can be developed in the context of paradoxes which arise in voting theory. Also, an application to the notion of probability signature may be of interest, in the field of systems reliability.

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来源期刊

Advances in Applied Probability 数学-统计学与概率论

CiteScore

2.00

自引率

0.00%

发文量

审稿时长

6-12 weeks

期刊介绍： The Advances in Applied Probability has been published by the Applied Probability Trust for over four decades, and is a companion publication to the Journal of Applied Probability. It contains mathematical and scientific papers of interest to applied probabilists, with emphasis on applications in a broad spectrum of disciplines, including the biosciences, operations research, telecommunications, computer science, engineering, epidemiology, financial mathematics, the physical and social sciences, and any field where stochastic modeling is used. A submission to Applied Probability represents a submission that may, at the Editor-in-Chief’s discretion, appear in either the Journal of Applied Probability or the Advances in Applied Probability. Typically, shorter papers appear in the Journal, with longer contributions appearing in the Advances.