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 |
| Reference manual: | robin.pdf |
| Vignettes: |
robin |
| Package source: | robin_0.99.1.tar.gz |
| Windows binaries: | r-devel: 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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