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noisySBM  

Noisy Stochastic Block Mode: Graph Inference by Multiple Testing
View on CRAN: Click here


Download and install noisySBM package within the R console
Install from CRAN:
install.packages("noisySBM")

Install from Github:
library("remotes")
install_github("cran/noisySBM")

Install by package version:
library("remotes")
install_version("noisySBM", "0.1.4")



Attach the package and use:
library("noisySBM")
Maintained by
Tabea Rebafka
[Scholar Profile | Author Map]
First Published: 2020-12-16
Latest Update: 2020-12-16
Description:
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) .
How to cite:
Tabea Rebafka (2020). noisySBM: Noisy Stochastic Block Mode: Graph Inference by Multiple Testing. R package version 0.1.4, https://cran.r-project.org/web/packages/noisySBM. Accessed 11 May. 2025.
Previous versions and publish date:
No previous versions
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Complete documentation for noisySBM
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