Package: missSBM
Type: Package
Title: Handling Missing Data in Stochastic Block Models
Version: 1.1.0
Authors@R: c(
  person("Julien", "Chiquet", role = c("aut", "cre"), email = "julien.chiquet@inrae.fr",
      comment = c(ORCID = "0000-0002-3629-3429")),
  person("Pierre", "Barbillon", role = "aut", email = "pierre.barbillon@agroparistech.fr",
      comment = c(ORCID = "0000-0002-7766-7693")),
  person("Timothée", "Tabouy", role = "aut", email = "timothee.tabouy@agroparistech.fr"),
  person("Jean-Benoist", "Léger", role = "ctb", email = "jbleger@hds.utc.fr", comment = "provided C++ implementaion of K-means"),
  person("François", "Gindraud", role = "ctb", email = "francois.gindraud@gmail.com", comment = "provided C++ interface to NLopt"),
  person("großBM team", role = c("ctb"))
  )
Maintainer: Julien Chiquet <julien.chiquet@inrae.fr>
Description: When a network is partially observed (here, NAs in the adjacency matrix rather than 1 or 0 
  due to missing information between node pairs), it is possible to account for the underlying process
  that generates those NAs. 'missSBM', presented in 'Barbillon, Chiquet and Tabouy' (2022) <doi:10.18637/jss.v101.i12>,
  adjusts the popular stochastic block model from network data sampled under various missing data conditions, 
  as described in 'Tabouy, Barbillon and Chiquet' (2019) <doi:10.1080/01621459.2018.1562934>.
URL: https://grosssbm.github.io/missSBM/
BugReports: https://github.com/grossSBM/missSBM/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.4.0)
Imports: Rcpp, methods, igraph, ggplot2, future.apply, R6, rlang, sbm,
        magrittr, Matrix, RSpectra
LinkingTo: Rcpp, RcppArmadillo
Collate: 'utils_missSBM.R' 'R6Class-networkSampling.R'
        'R6Class-networkSampling_fit.R' 'R6Class-simpleSBM_fit.R'
        'R6Class-missSBM_fit.R' 'R6Class-missSBM_collection.R'
        'R6Class-networkSampler.R' 'R6Class-partlyObservedNetwork.R'
        'RcppExports.R' 'er_network.R' 'estimateMissSBM.R'
        'frenchblog2007.R' 'kmeans.R' 'missSBM-package.R'
        'observeNetwork.R' 'war.R'
Suggests: aricode, blockmodels, corrplot, future, testthat (>= 2.1.0),
        covr, knitr, rmarkdown, spelling
VignetteBuilder: knitr
Language: en-US
Config/roxygen2/version: 8.0.0
NeedsCompilation: yes
Packaged: 2026-07-21 16:34:48 UTC; jchiquet
Author: Julien Chiquet [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-3629-3429>),
  Pierre Barbillon [aut] (ORCID: <https://orcid.org/0000-0002-7766-7693>),
  Timothée Tabouy [aut],
  Jean-Benoist Léger [ctb] (provided C++ implementaion of K-means),
  François Gindraud [ctb] (provided C++ interface to NLopt),
  großBM team [ctb]
Repository: CRAN
Date/Publication: 2026-07-21 22:40:02 UTC
Built: R 4.6.1; x86_64-w64-mingw32; 2026-09-02 04:30:15 UTC; windows
Archs: x64
