doi:10.48550/arXiv.1602.07587>, 'Barbillon et al.' (2020) <doi:10.1111/rssa.12193> and 'Bar-Hen et al.' (2020) <doi:10.48550/arXiv.1807.10138>.">

sbm: Stochastic Blockmodels (original) (raw)

A collection of tools and functions to adjust a variety of stochastic blockmodels (SBM). Supports at the moment Simple, Bipartite, 'Multipartite' and Multiplex SBM (undirected or directed with Bernoulli, Poisson or Gaussian emission laws on the edges, and possibly covariate for Simple and Bipartite SBM). See Léger (2016) <doi:10.48550/arXiv.1602.07587>, 'Barbillon et al.' (2020) <doi:10.1111/rssa.12193> and 'Bar-Hen et al.' (2020) <doi:10.48550/arXiv.1807.10138>.

Version: 0.4.7
Depends: R (≥ 3.5.0)
Imports: alluvial, magrittr, dplyr, purrr, blockmodels, R6, Rcpp, igraph, ggplot2, GREMLINS, stringr, rlang, reshape2, prodlim
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, spelling, knitr, rmarkdown, aricode, covr
Published: 2024-09-16
DOI: 10.32614/CRAN.package.sbm
Author: Julien Chiquet ORCID iD [aut, cre], Sophie Donnet ORCID iD [aut], großBM team [ctb], Pierre Barbillon ORCID iD [aut]
Maintainer: Julien Chiquet <julien.chiquet at inrae.fr>
BugReports: https://github.com/GrossSBM/sbm/issues
License: GPL (≥ 3)
URL: https://grosssbm.github.io/sbm/
NeedsCompilation: yes
Language: en-US
Materials: README NEWS
CRAN checks: sbm results

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