Empirical analysis of the dependence structure in traffic data using copula function

Ting-ting Zhao, Y. Nie, Xing Wu, Yi Zhang
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引用次数: 2

Abstract

Statistical distributions of link and path travel times are important inputs to reliability-sensitive transportation models. This paper proposes to use copula functions for specifying and calibrating a tractable dependence structure for link travel times. Our empirical study indicates that travel time data tend to have a quasi-tail dependence structure, which is inconsistent with those embedded in commonly used copulas. This means that comparing with traditional fields using copula function, such as financial, traffic data demonstrate special features. A new copula function needs to be proposed to model this newly discovered feature.
基于copula函数的交通数据依赖结构实证分析
链路和路径运行时间的统计分布是可靠性敏感运输模型的重要输入。本文提出用联结函数来指定和标定一种可处理的链路行程时间依赖结构。我们的实证研究表明,旅行时间数据倾向于具有准尾巴依赖结构,这与常用copula中嵌入的数据不一致。这意味着与传统的使用copula函数的领域(如金融)相比,交通数据表现出了特殊的特点。需要提出一个新的联结函数来对这个新发现的特征进行建模。
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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