graphclust: Hierarchical Graph Clustering for a Collection of Networks

Graph clustering using an agglomerative algorithm to maximize the integrated classification likelihood criterion and a mixture of stochastic block models. The method is described in the article "Model-based graph clustering of a collection of networks using an agglomerative algorithm" by T. Rebafka (2022) <arXiv:2211.02314>.

Version:	1.0.1
Imports:	blockmodels, igraph, parallel, sClust
Published:	2023-01-12
Author:	Tabea Rebafka [aut, cre]
Maintainer:	Tabea Rebafka <tabea.rebafka at sorbonne-universite.fr>
License:	GPL-2
NeedsCompilation:	no
CRAN checks:	graphclust results

Documentation:

Reference manual:

graphclust.pdf

Downloads:

Package source:	graphclust_1.0.1.tar.gz
Windows binaries:	r-devel: graphclust_1.0.1.zip, r-release: graphclust_1.0.1.zip, r-oldrel: graphclust_1.0.1.zip
macOS binaries:	r-release (arm64): graphclust_1.0.1.tgz, r-oldrel (arm64): graphclust_1.0.1.tgz, r-release (x86_64): graphclust_1.0.1.tgz, r-oldrel (x86_64): graphclust_1.0.1.tgz

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