Source estimation for propagation processes on complex networks with an application to delays in public transportation systems
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..
|Keywords||Complex network, Delay spreading, Propagation process, Public transportation network, Source detection, Statistical network analysis|
|Persistent URL||dx.doi.org/10.1111/rssc.12176, hdl.handle.net/1765/96002|
|Series||ERIM Top-Core Articles|
|Journal||Royal Statistical Society. Journal. Series C: Applied Statistics|
Manitz, J. (Juliane), Harbering, J. (Jonas), Schmidt, M.E, Kneib, T, & Schöbel, A. (2017). Source estimation for propagation processes on complex networks with an application to delays in public transportation systems. Royal Statistical Society. Journal. Series C: Applied Statistics, 66(3), 521–536. doi:10.1111/rssc.12176