Performs network-based source estimation. Different approaches are available: effective distance median, recursive backtracking, and centrality-based source estimation. Additionally, we provide public transportation network data as well as methods for data preparation, source estimation performance analysis and visualization.
You can install the latest production version from CRAN
install.packages("NetOrigin", dependencies = TRUE)or the current development version from GitHub
library("devtools")
install_github("jmanitz/NetOrigin")Then, load the package
library("NetOrigin")-
Manitz, J., J. Harbering, M. Schmidt, T. Kneib, and A. Schoebel (2017): Source Estimation for Propagation Processes on Complex Networks with an Application to Delays in Public Transportation Systems. Journal of Royal Statistical Society C (Applied Statistics), 66: 521–536.
-
Manitz, J., Kneib, T., Schlather, M., Helbing, D. and Brockmann, D. (2014) Origin detection during food-borne disease outbreaks - a case study of the 2011 EHEC/HUS outbreak in Germany. PLoS Currents Outbreaks, 1. <DOI: 10.1371/currents.outbreaks.f3fdeb08c5b9de7c09ed9cbcef5f01f2>
-
Comin, C. H. and da Fontoura Costa, L. (2011) Identifying the starting point of a spreading process in complex networks. Physical Review E, 84. <DOI: 10.1103/PhysRevE.84.056105>
To cite package ‘NetOrigin’ in publications use:
Juliane Manitz (2018). NetOrigin: Origin Estimation for Propagation Processes on Complex Networks. R package version 1.0-3. https://CRAN.R-project.org/package=NetOrigin
Use toBibtex(citation("NetOrigin")) in R to extract BibTeX references.