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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 clustering of multiple networks with a hierarchical algorithm" by T. Rebafka (2022) <doi:10.48550/arXiv.2211.02314>.
| Version: | 1.3 |
| Imports: | blockmodels, igraph, parallel, sClust |
| Published: | 2023-06-07 |
| Author: | Tabea Rebafka [aut, cre] |
| Maintainer: | Tabea Rebafka <tabea.rebafka at sorbonne-universite.fr> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | graphclust results |
| Reference manual: | graphclust.pdf |
| Package source: | graphclust_1.3.tar.gz |
| Windows binaries: | r-devel: graphclust_1.3.zip, r-release: graphclust_1.3.zip, r-oldrel: graphclust_1.3.zip |
| macOS binaries: | r-release (arm64): graphclust_1.3.tgz, r-oldrel (arm64): graphclust_1.3.tgz, r-release (x86_64): graphclust_1.3.tgz, r-oldrel (x86_64): graphclust_1.3.tgz |
| Old sources: | graphclust archive |
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