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>.
|Author||Tabea Rebafka [aut, cre], Etienne Roquain [ctb], Fanny Villers [aut]|
|Maintainer||Tabea Rebafka <firstname.lastname@example.org>|
|Package repository||View on CRAN|
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