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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 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 languageEnglish (US)
Title of host publicationProceedings of 2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages38-42
Number of pages5
ISBN (Electronic)9781479960583
DOIs
StatePublished - Nov 17 2014
Event2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014 - Qingdao, China
Duration: Oct 8 2014Oct 10 2014

Publication series

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

Other

Other2014 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2014
CountryChina
CityQingdao
Period10/8/1410/10/14

ASJC Scopus subject areas

  • Management of Technology and Innovation
  • Information Systems

Fingerprint Dive into the research topics of 'Empirical analysis of the dependence structure in traffic data using copula function'. Together they form a unique fingerprint.

Cite this