Package: mimiSBM 0.0.1.3

mimiSBM: Mixture of Multilayer Integrator Stochastic Block Models

Our approach uses a mixture of multilayer stochastic block models to group co-membership matrices with similar information into components and to partition observations into different clusters. See De Santiago (2023, ISBN: 978-2-87587-088-9).

Authors:Kylliann De Santiago [aut, cre], Marie Szafranski [aut], Christophe Ambroise [aut]

mimiSBM_0.0.1.3.tar.gz
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mimiSBM.pdf |mimiSBM.html✨
mimiSBM/json (API)

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

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.70 score 126 downloads 26 exports 4 dependencies

Last updated 11 months agofrom:26d0910b0a. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 30 2024
R-4.5-winOKOct 30 2024
R-4.5-linuxOKOct 30 2024
R-4.4-winOKOct 30 2024
R-4.4-macOKOct 30 2024
R-4.3-winOKOct 30 2024
R-4.3-macOKOct 30 2024

Exports:BayesianMixture_SBM_modelCEMdiag_nullefit_SBM_per_layerfit_SBM_per_layer_parallellab_switchinglog_SoftmaxLoss_BayesianMSBMMat_lien_alphamimiSBMmultinomial_lbeta_functionone_hot_errormachinepartition_K_barreplot_adjacencyrMSBMrSMB_partitionsort_Ztranspotrig_supupdate_beta_bayesianupdate_eta_bayesianupdate_tau_bayesianupdate_theta_bayesianupdate_u_bayesianupdate_xi_bayesianVBEM_step

Dependencies:blockmodelsdigestRcppRcppArmadillo

Simulations

Rendered fromSimulations.Rmdusingknitr::rmarkdownon Oct 30 2024.

Last update: 2024-01-10
Started: 2024-01-10