Description Usage Arguments Value Author(s) References Examples
Computes the flow.frac for each community in the network. The values are equivalent to the community's eigenvector centrality
1 | comm.eigen(A, comm, weighted = TRUE)
|
A |
An adjacency matrix |
comm |
A vector or matrix corresponding to the community each node belongs to |
weighted |
Is the network weighted?
Defaults to |
A vector of community eigenvector centrality values for each specified community in the network (larger values suggest more central positioning)
Alexander Christensen <alexpaulchristensen@gmail.com>
Giscard, P. L., & Wilson, R. C. (2018). A centrality measure for cycles and subgraphs II. Applied Network Science, 3, 9.
1 2 3 4 5 6 | # Pearson's correlation only for CRAN checks
A <- TMFG(neoOpen, normal = FALSE)$A
comm <- igraph::walktrap.community(convert2igraph(abs(A)))$membership
result <- comm.eigen(A, comm)
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