J.gamma

<p>parameters of the Gamma distribution</p>

param

<p>evaluate the objective in the Gamma model</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

J.gamma: evaluate the objective in the Gamma model

Description

Usage

Arguments

Value