Package: sbm 0.4.7

Julien Chiquet

sbm: Stochastic Blockmodels

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>.

Authors:Julien Chiquet [aut, cre], Sophie Donnet [aut], großBM team [ctb], Pierre Barbillon [aut]

sbm_0.4.7.tar.gz
sbm_0.4.7.zip(r-4.5)sbm_0.4.7.zip(r-4.4)sbm_0.4.7.zip(r-4.3)
sbm_0.4.7.tgz(r-4.5-x86_64)sbm_0.4.7.tgz(r-4.5-arm64)sbm_0.4.7.tgz(r-4.4-x86_64)sbm_0.4.7.tgz(r-4.4-arm64)sbm_0.4.7.tgz(r-4.3-x86_64)sbm_0.4.7.tgz(r-4.3-arm64)
sbm_0.4.7.tar.gz(r-4.5-noble)sbm_0.4.7.tar.gz(r-4.4-noble)
sbm_0.4.7.tgz(r-4.4-emscripten)sbm_0.4.7.tgz(r-4.3-emscripten)
sbm.pdf |sbm.html✨
sbm/json (API)
NEWS

# Install 'sbm' in R:
install.packages('sbm', repos = c('https://grosssbm.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/grosssbm/sbm/issues

Pkgdown site:https://grosssbm.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda-Forge:

network-analysissbmstochastic-block-modelcpp

8.45 score 16 stars 2 packages 98 scripts 539 downloads 22 exports 62 dependencies

Last updated 6 months agofrom:a21af071cc. Checks:11 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 13 2025
R-4.5-win-x86_64OKFeb 13 2025
R-4.5-mac-x86_64OKFeb 13 2025
R-4.5-mac-aarch64OKFeb 13 2025
R-4.5-linux-x86_64OKFeb 13 2025
R-4.4-win-x86_64OKFeb 13 2025
R-4.4-mac-x86_64OKFeb 13 2025
R-4.4-mac-aarch64OKFeb 13 2025
R-4.3-win-x86_64OKFeb 13 2025
R-4.3-mac-x86_64OKFeb 13 2025
R-4.3-mac-aarch64OKFeb 13 2025

Exports:%>%BipartiteSBMBipartiteSBM_fitdefineSBMestimateBipartiteSBMestimateMultipartiteSBMestimateMultiplexSBMestimateSimpleSBMis_SBMMultipartiteSBMMultipartiteSBM_fitMultiplexSBM_fitplotAlluvialplotMyMatrixplotMyMultipartiteMatrixplotMyMultiplexMatrixsampleBipartiteSBMsampleMultipartiteSBMsampleMultiplexSBMsampleSimpleSBMSimpleSBMSimpleSBM_fit

Dependencies:alluvialaricodeblockmodelsclicodetoolscolorspacecpp11data.tablediagramdigestdplyrfansifarverfuturefuture.applygenericsggplot2globalsglueGREMLINSgtableigraphisobandKernSmoothlabelinglatticelavalifecyclelistenvmagrittrMASSMatrixmgcvmunsellnlmenumDerivparallellypbmcapplypillarpkgconfigplyrprodlimprogressrpurrrR6RColorBrewerRcppRcppArmadilloreshape2rlangscalesshapeSQUAREMstringistringrsurvivaltibbletidyselectutf8vctrsviridisLitewithr

Multipartite Stochastic Block Models

team großBM

Rendered fromMultipartite_EcologicalNetwork.Rmdusingknitr::rmarkdownon Feb 13 2025.

Last update: 2022-09-12
Started: 2020-12-18

Simple and Bipartite Stochastic Block Models

team großBM

Rendered fromSBM_fungus_tree_network.Rmdusingknitr::rmarkdownon Feb 13 2025.

Last update: 2022-09-12
Started: 2020-06-25

Stochastic Block Models for Multiplex networks

team großBM

Rendered fromMultiplex_allianceNwar_case_study.Rmdusingknitr::rmarkdownon Feb 13 2025.

Last update: 2023-01-07
Started: 2021-05-19

Stochastic Block Models for Multiplex networks

team großBM

Rendered fromMultiplexNetwork_principle.Rmdusingknitr::rmarkdownon Feb 13 2025.

Last update: 2022-09-12
Started: 2021-05-05