Description Usage Arguments Details Value Author(s) References Examples
Computes the participation coefficient for each node. The participation coefficient measures the strength of a node's connections within its community. Positive and negative signed weights for participation coefficients are computed separately.
1 | participation(A, comm = c("walktrap", "louvain"))
|
A |
Network adjacency matrix |
comm |
A vector of corresponding to each item's community.
Defaults to |
Values closer to 1 suggest greater within-community connectivity and values closer to 0 suggest greater between-community connectivity
Returns a list containing:
overall |
Participation coefficient without signs considered |
positive |
Participation coefficient with only positive sign |
negative |
Participation coefficient with only negative sign |
Alexander Christensen <alexpaulchristensen@gmail.com>
Guimera, R., & Amaral, L. A. N. (2005). Functional cartography of complex metabolic networks. Nature, 433, 895-900.
Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: Uses and interpretations. NeuroImage, 52, 1059-1069.
1 2 3 4 5 6 7 8 9 10 | #theoretical factors
comm <- rep(1:8, each = 6)
# Pearson's correlation only for CRAN checks
A <- TMFG(neoOpen, normal = FALSE)$A
pc <- participation(A, comm = comm)
# Walktrap factors
wpc <- participation(A, comm = "walktrap")
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