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) .


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("robin")

0.99.1 by Valeria Policastro, a month ago


https://github.com/ValeriaPolicastro/robin


Browse source code at https://github.com/cran/robin


Authors: Valeria Policastro [aut, cre] , Dario Righelli [aut] , Luisa Cutillo [aut] , Italia De Feis [aut] , Annamaria Carissimo [aut]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports ggplot2, networkD3, DescTools, fdatest, methods

Depends on igraph, gprege

Suggests devtools, cowplot, knitr, rmarkdown, testthat


See at CRAN