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Variational Expectation-Maximization algorithm to fit the noisy stochastic block model to an observed dense graph and to perform a node clustering. Moreover, a graph inference procedure to recover the underlying binary graph. This procedure comes with a control of the false discovery rate. The method is described in the article "Powerful graph inference with false discovery rate control" by T. Rebafka, E. Roquain, F. Villers (2020) <arXiv:1907.10176>.
Package details |
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Author | Tabea Rebafka [aut, cre], Etienne Roquain [ctb], Fanny Villers [aut] |
Maintainer | Tabea Rebafka <tabea.rebafka@sorbonne-universite.fr> |
License | GPL-2 |
Version | 0.1.4 |
Package repository | View on CRAN |
Installation |
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