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

Tingting Zhao; Yu Nie; Xing Wu; Yi Zhang

doi:10.1109/SOLI.2014.6960690

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

Tingting Zhao^*, Yu Nie, Xing Wu, Yi Zhang

^*Corresponding author for this work

Civil and Environmental Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

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.

Original language	English (US)
Title of host publication	Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	38-42
Number of pages	5
ISBN (Electronic)	9781479960583
DOIs	https://doi.org/10.1109/SOLI.2014.6960690
State	Published - Nov 17 2014
Event	2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014 - Qingdao, China Duration: Oct 8 2014 → Oct 10 2014

Publication series

Name	Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014

Other

Other	2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014
Country/Territory	China
City	Qingdao
Period	10/8/14 → 10/10/14

ASJC Scopus subject areas

Management of Technology and Innovation
Information Systems

Access to Document

10.1109/SOLI.2014.6960690

Cite this

Zhao, T., Nie, Y., Wu, X., & Zhang, Y. (2014). Empirical analysis of the dependence structure in traffic data using copula function. In Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014 (pp. 38-42). Article 6960690 (Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SOLI.2014.6960690

Zhao, Tingting ; Nie, Yu ; Wu, Xing et al. / Empirical analysis of the dependence structure in traffic data using copula function. Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 38-42 (Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014).

@inproceedings{2e4bd34ac67942ceb709d624e3643212,

title = "Empirical analysis of the dependence structure in traffic data using copula function",

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.",

author = "Tingting Zhao and Yu Nie and Xing Wu and Yi Zhang",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014 ; Conference date: 08-10-2014 Through 10-10-2014",

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doi = "10.1109/SOLI.2014.6960690",

language = "English (US)",

series = "Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014",

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Zhao, T, Nie, Y, Wu, X & Zhang, Y 2014, Empirical analysis of the dependence structure in traffic data using copula function. in Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014., 6960690, Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014, Institute of Electrical and Electronics Engineers Inc., pp. 38-42, 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014, Qingdao, China, 10/8/14. https://doi.org/10.1109/SOLI.2014.6960690

Empirical analysis of the dependence structure in traffic data using copula function. / Zhao, Tingting; Nie, Yu; Wu, Xing et al.
Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 38-42 6960690 (Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Wu, Xing

AU - Zhang, Yi

PY - 2014/11/17

Y1 - 2014/11/17

N2 - 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.

AB - 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.

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BT - Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014

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Zhao T, Nie Y, Wu X, Zhang Y. Empirical analysis of the dependence structure in traffic data using copula function. In Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 38-42. 6960690. (Proceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014). doi: 10.1109/SOLI.2014.6960690

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

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