Description Usage Arguments Value Author(s) References Examples
Identify statistically significant communities in undirected networks
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Adj.Matrix |
Adjacency matrix of the network for which you'd like to find communities |
alpha |
False discovery rate. Value between 0 and 1 that sets an upper limit on the false discovery rate of the hypothesis testing procedure in ESSC |
Null |
The null distribution used for comparing the observed number of connections between a single vertex and a community of vertices. Can be set to either "Binomial" or "Poisson." Default is "Binomial" |
Num.Samples |
The number of randomly selected neighborhoods used to initiate the ESSC algorithm. The maximum number is the number of vertices in Adj.Matrix. Defaults to the number of vertices in Adj.Matrix |
a list containing the objects
Communities: a list of identified communities
Background: a numeric vector identifying vertices that did not belong to any statistically significant community
James D. Wilson
Wilson, James D.,Wang, Simi, Mucha, Peter J., Bhamidi, Shankar, and Nobel, Andrew B. (2014). <e2><80><9c>A testing based extraction algorithm for identifying significant communities in networks.<e2><80><9d> The Annals of Applied Statistics Vol. 8, No. 3, 1853-1891
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