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
mimiSBM_0.0.1.3.zip(r-4.7-any)mimiSBM_0.0.1.3.zip(r-4.6-any)mimiSBM_0.0.1.3.zip(r-4.5-any)
mimiSBM_0.0.1.3.tgz(r-4.6-any)mimiSBM_0.0.1.3.tgz(r-4.5-any)
mimiSBM_0.0.1.3.tar.gz(r-4.7-any)mimiSBM_0.0.1.3.tar.gz(r-4.6-any)
mimiSBM_0.0.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
mimiSBM/json (API)

# Install 'mimiSBM' in R:

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

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 213 downloads 26 exports 4 dependencies

Last updated from:26d0910b0a. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	174
source / vignettes	OK	174
linux-release	OK	171
macos-release	OK	146
macos-oldrel	OK	122
windows-devel	OK	69
windows-release	OK	76
windows-oldrel	OK	59
wasm-release	OK	103

Exports:BayesianMixture_SBM_model CEM diag_nulle fit_SBM_per_layer fit_SBM_per_layer_parallel lab_switching log_Softmax Loss_BayesianMSBM Mat_lien_alpha mimiSBM multinomial_lbeta_function one_hot_errormachine partition_K_barre plot_adjacency rMSBM rSMB_partition sort_Z transpo trig_sup update_beta_bayesian update_eta_bayesian update_tau_bayesian update_theta_bayesian update_u_bayesian update_xi_bayesian VBEM_step

Dependencies:blockmodels digest Rcpp RcppArmadillo

Simulations

Data generation | First simulation: no label-switching | Setup of parameters | Simulation | Second simulation: label-switching

Rendered fromSimulations.Rmdusingknitr::rmarkdown

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

Citation

Readme and manuals

Help Manual

Help page	Topics
mimiSBM model for fixed K and Q	BayesianMixture_SBM_model
Clustering Matrix : One hot encoding	CEM
Diagonal coefficient to 0 on each slice given the 3rd dimension.	diag_nulle
SBM on each layer	fit_SBM_per_layer
SBM on each layer - parallelized	fit_SBM_per_layer_parallel
Initialization of mimiSBM parameters	initialisation_params_bayesian
Label Switching	lab_switching
log softmax of matrices (by row)	log_Softmax
mimiSBM Evidence Lower BOund	Loss_BayesianMSBM
Create probality-component list for clustering per view component.	Mat_lien_alpha
Mixture of Multilayer Integrator SBM (mimiSBM)	mimiSBM
Calculation of Log multinomial Beta value.	multinomial_lbeta_function
One Hot Encoding with Error machine	one_hot_errormachine
Create a link between final clustering and clustering per view component.	partition_K_barre
Plot adjacency matrices	plot_adjacency
Simulate data from the mimiSBM generative model.	rMSBM
Simulation of mixture multilayer Stochastick block model	rSMB_partition
Sort the clustering matrix	sort_Z
Transposition of an array	transpo
Upper triangular Matrix/Array	trig_sup
Update of bayesian parameter beta	update_beta_bayesian
Update of bayesian parameter eta	update_eta_bayesian
Update of bayesian parameter tau	update_tau_bayesian
Update of bayesian parameter theta	update_theta_bayesian
Update of bayesian parameter u	update_u_bayesian
Update of bayesian parameter xi	update_xi_bayesian
Variational Bayes Expectation Maximization	VBEM_step

Package: mimiSBM 0.0.1.3

mimiSBM: Mixture of Multilayer Integrator Stochastic Block Models

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)