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Source estimation for propagation processes on complex networks with an application to delays in public transportation systems
Author(s) -
Manitz Juliane,
Harbering Jonas,
Schmidt Marie,
Kneib Thomas,
Schöbel Anita
Publication year - 2017
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/rssc.12176
Subject(s) - centrality , computer science , identification (biology) , backtracking , process (computing) , estimation , complex network , data mining , algorithm , systems engineering , engineering , mathematics , botany , biology , operating system , combinatorics , world wide web
Summary 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.