doi:10.1016/j.csda.2025.108228>.">

JANE: Just Another Latent Space Network Clustering Algorithm (original) (raw)

Fit latent space network cluster models using an expectation-maximization algorithm. Enables flexible modeling of unweighted or weighted network data (with or without noise edges), supporting both directed and undirected networks (with or without degree and strength heterogeneity). Designed to handle large networks efficiently, it allows users to explore network structure through latent space representations, identify clusters (i.e., community detection) within network data, and simulate networks with varying clustering, connectivity patterns, and noise edges. Methodology for the implementation is described in Arakkal and Sewell (2025) <doi:10.1016/j.csda.2025.108228>.

Version: 2.1.0
Depends: R (≥ 4.1.0)
Imports: Rcpp (≥ 1.0.10), Matrix, extraDistr, mclust, scales, aricode, stringdist, utils, splines, rlang, future.apply, future, progressr, progress, igraph, methods
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2025-11-03
DOI: 10.32614/CRAN.package.JANE
Author: Alan Arakkal ORCID iD [aut, cre, cph], Daniel Sewell ORCID iD [aut]
Maintainer: Alan Arakkal
BugReports: https://github.com/a1arakkal/JANE/issues
License: GPL (≥ 3)
URL: https://a1arakkal.github.io/JANE/,https://github.com/a1arakkal/JANE
NeedsCompilation: yes
Citation: JANE citation info
Materials: NEWS
CRAN checks: JANE results

Documentation:

Downloads:

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=JANEto link to this page.