Package: noisySBM
Type: Package
Title: Noisy Stochastic Block Mode: Graph Inference by Multiple Testing
Version: 0.1.4
Authors@R: 
  c(person(given = "Tabea",
           family = "Rebafka",
           role = c("aut", "cre"),
           email = "tabea.rebafka@sorbonne-universite.fr"),
    person(given = "Etienne",
           family = "Roquain",
           role = "ctb"),
    person(given = "Fanny",
           family = "Villers",
           role = "aut"))
Author: Tabea Rebafka [aut, cre],
  Etienne Roquain [ctb],
  Fanny Villers [aut]
Maintainer: Tabea Rebafka <tabea.rebafka@sorbonne-universite.fr>
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) <arXiv:1907.10176>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: parallel, gtools, ggplot2, RColorBrewer
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2020-12-14 21:10:07 UTC; tabea
Repository: CRAN
Date/Publication: 2020-12-16 10:40:06 UTC
Built: R 4.0.5; ; 2022-04-18 04:32:18 UTC; windows
