addRowToTau

<p>split group q of provided tau randomly into two into</p>

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>.

Tabea Rebafka

noisySBM

Noisy Stochastic Block Mode: Graph Inference by Multiple Testing

addRowToTau: split group q of provided tau randomly into two into

Description

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