robin: ROBustness in Network

Many community detection algorithms have been developed in network analysis. However, their applications leave unaddressed the statistical validation of the results, for this reason we developed ROBIN (ROBustness In Network), a useful method for the validation of community detection. It has a double aim, it studies the robustness of a single community detection algorithm and compares two community detection algorithms to understand which provides the best partition. Reference in Annamaria Carissimo, Luisa Cutillo, Italia De Feis (2018) <doi:10.1016/j.csda.2017.10.006>.

Version: 0.99.1
Depends: R (≥ 3.5), igraph, gprege
Imports: ggplot2, networkD3, DescTools, fdatest, methods
Suggests: devtools, cowplot, knitr, rmarkdown, testthat (≥ 2.1.0)
Published: 2019-10-24
Author: Valeria Policastro [aut, cre], Dario Righelli [aut], Luisa Cutillo [aut], Italia De Feis [aut], Annamaria Carissimo [aut]
Maintainer: Valeria Policastro <valeria.policastro at gmail.com>
License: MIT + file LICENSE
URL: https://github.com/ValeriaPolicastro/robin
NeedsCompilation: no
Materials: README NEWS
CRAN checks: robin results

Downloads:

Reference manual: robin.pdf
Vignettes: robin
Package source: robin_0.99.1.tar.gz
Windows binaries: r-devel: robin_0.99.1.zip, r-devel-gcc8: robin_0.99.1.zip, r-release: robin_0.99.1.zip, r-oldrel: robin_0.99.1.zip
OS X binaries: r-release: not available, r-oldrel: not available
Old sources: robin archive

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