This repository contains the code to reproduce the results of the case study from the paper "Inferring High-Dimensional Dynamic Networks Changing with Multiple Covariates" by Louis Dijkstra, Arne Godt, and Ronja Foraita.
In order to reproduce the results as presented in the paper, run the run.R script.
All images used in the paper are saved in the folder results:
source("run.R")The CVN package can be installed from the GitHub repository
bips-hb@CVN.
Inferring High-Dimensional Dynamic Networks Changing with Multiple Covariates
L.J. Dijkstra, A. Godt & R. Foraita (2024)
https://arxiv.org/abs/2407.19978
The authors gratefully acknowledge the financial support of the German Research Foundation (DFG -- Project FO 1045/2-1). The first author thanks Professor Caroline Uhler and her team for the valuable and stimulating discussions. We sincerely thank the KiKME committee for generously providing the data used in our case study.
The KiKME dataset analyzed within this case study is available from the committee of the ISIBELa project (Intrinsic radiation sensitivity: Identification of biological and epidemiological long-term effects, principal investigators: Maria Blettner and Heinz Schmidberger, University Medical Center of the Johannes Gutenberg-University Mainz) upon reasonable request.
Ronja Foraita
Leibniz Institute for Prevention Research & Epidemiology
E-mail: foraita (at) leibniz-bips.de