jchiquet/missSBM: Handling Missing Data in Stochastic Block Models

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>.

Getting started

Package details

MaintainerJulien Chiquet <julien.chiquet@inrae.fr>
LicenseGPL-3
Version1.0.4
URL https://grosssbm.github.io/missSBM/
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("jchiquet/missSBM")
jchiquet/missSBM documentation built on Oct. 25, 2023, 5:30 a.m.