Network changepoint analysis for undirected network data. The package implements a hidden Markov network change point model (Park and Sohn (2020)). Functions for break number detection using the approximate marginal likelihood and WAIC are also provided. Version 1.1.0 includes high-performance C++ implementations via 'Rcpp'/'RcppArmadillo' for 5-15x faster MCMC sampling, along with modern 'ggplot2'-based visualizations with colorblind-friendly palettes.
| Version: |
1.1.0 |
| Depends: |
R (≥ 3.5.0), MCMCpack, ggplot2 |
| Imports: |
Rcpp (≥ 1.0.0), Rmpfr, abind, mvtnorm, tidyr, igraph, qgraph, network, stats, MASS, methods, RColorBrewer, ggrepel, rlang, GGally, patchwork, viridis |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
sna, lifecycle |
| Published: |
2026-04-07 |
| DOI: |
10.32614/CRAN.package.NetworkChange |
| Author: |
Jong Hee Park [aut, cre],
Yunkyu Sohn [aut] |
| Maintainer: |
Jong Hee Park <jongheepark at snu.ac.kr> |
| License: |
GPL-3 |
| NeedsCompilation: |
yes |
| In views: |
Bayesian |
| CRAN checks: |
NetworkChange results |