missSBM (0.2.1)

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' adjusts the popular stochastic block model from network data sampled under various missing data conditions, as described in Tabouy, Barbillon and Chiquet (2019) .

Maintainer: Julien Chiquet
Author(s): Julien Chiquet [aut, cre] (<https://orcid.org/0000-0002-3629-3429>), Pierre Barbillon [aut] (<https://orcid.org/0000-0002-7766-7693>), Timothe Tabouy [aut]

License: GPL-3

Uses: ape, corrplot, ggplot2, igraph, magrittr, nloptr, R6, Rcpp, testthat, knitr, rmarkdown, blockmodels, covr, aricode

Released about 1 month ago.