diversity {NetworkToolbox} | R Documentation |
Diversity Coefficient
Description
Computes the diversity coefficient for each node. The diversity coefficient measures a node's connections to communitites outside of its own community. Nodes that have many connections to other communities will have higher diversity coefficient values. Positive and negative signed weights for diversity coefficients are computed separately.
Usage
diversity(A, comm = c("walktrap", "louvain"))
Arguments
A |
Network adjacency matrix |
comm |
A vector of corresponding to each item's community.
Defaults to |
Details
Values closer to 1 suggest greater between-community connectivity and values closer to 0 suggest greater within-community connectivity
Value
Returns a list containing:
overall |
Diversity coefficient without signs considered |
positive |
Diversity coefficient with only positive sign |
negative |
Diversity coefficient with only negative sign |
Author(s)
Alexander Christensen <alexpaulchristensen@gmail.com>
References
Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: Uses and interpretations. NeuroImage, 52, 1059-1069.
Examples
# Pearson's correlation only for CRAN checks
A <- TMFG(neoOpen, normal = FALSE)$A
#theoretical communities
comm <- rep(1:8, each = 6)
gdiv <- diversity(A, comm = comm)
#walktrap communities
wdiv <- diversity(A, comm = "walktrap")