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noisySBM
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
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[Scholar Profile | Author Map]
All associated links for this package
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 02 Nov. 2026.
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Complete documentation for noisySBM
Functions, R codes and Examples using
the noisySBM R package
Some associated functions: ARI . ICL_Q . J.gamma . JEvalMstep . Mstep . VEstep . addRowToTau . classInd . convertGroupPair . convertGroupPairIdentifier . convertNodePair . correctTau . emv_gamma . fitNSBM . getBestQ . getRho . getTauql . graphInference . initialPoints . initialPointsByMerge . initialPointsBySplit . initialRho . initialTau . listNodePairs . lvaluesNSBM . mainVEM_Q . mainVEM_Q_par . modelDensity . plotGraphs . plotICL . q_delta_ql . qvaluesNSBM . res_exp . res_gamma . res_gauss . rnsbm . spectralClustering . tauDown . tauUp . tauUpdate . update_newton_gamma .
Some associated R codes: ARI.R . VEMalgorithm.R . VEMinitialization.R . auxiliaryFunctions.R . data.R . dataGeneration.R . testProcedure.R . Full noisySBM package functions and examples
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