Source estimation for propagation processes on complex networks with an application to delays in public transportation systems

Manitz J, Harbering J, Schmidt M, Kneib T, Schoebel A (2017)

Publication Type: Journal article

Publication year: 2017

Journal

Journal of the Royal Statistical Society Series C-Applied Statistics Royal Statistical Society

Book Volume: 66

Pages Range: 521-536

Journal Issue: 3

DOI: 10.1111/rssc.12176

Abstract

The correct identification of the source of a propagation process is crucial in many research fields. As a specific application, we consider source estimation of delays in public transportation networks. We propose two approaches: an effective distance median and a backtracking method. The former is based on a structurally generic effective distance-based approach for the identification of infectious disease origins, and the latter is specifically designed for delay propagation. We examine the performance of both methods in simulation studies and in an application to the German railway system, and we compare the results with those of a centrality-based approach for source detection.

Involved external institutions

Georg-August-Universität Göttingen DE Germany (DE) Erasmus University Rotterdam (EUR) / Erasmus Universiteit Rotterdam NL Netherlands (NL)

How to cite

APA:

Manitz, J., Harbering, J., Schmidt, M., Kneib, T., & Schoebel, A. (2017). Source estimation for propagation processes on complex networks with an application to delays in public transportation systems. Journal of the Royal Statistical Society Series C-Applied Statistics, 66(3), 521-536. https://doi.org/10.1111/rssc.12176

MLA:

Manitz, Juliane, et al. "Source estimation for propagation processes on complex networks with an application to delays in public transportation systems." Journal of the Royal Statistical Society Series C-Applied Statistics 66.3 (2017): 521-536.

BibTeX: Download