NetworkToolbox (version 1.1.2)

diversity: 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, factors = c("walktrap", "louvain"))

Arguments

A

Network adjacency matrix

factors

A vector of corresponding to each item's factor. Defaults to "walktrap" for the walktrap community detection algorithm. Set to "louvain" for the louvain community detection algorithm. Can also be set to user-specified factors (see examples)

Value

Returns a list of overall (signs not considered; overall), negative (negative), and positive (positive) gateway coefficients

References

Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: Uses and interpretations. Neuroimage, 52(3), 1059-1069.

Examples

# NOT RUN {
#theoretical factors
factors <- c(rep(1,8), rep(2,8), rep(3,8), rep(4,8), rep(5,8), rep(6,8))

A <- TMFG(neoOpen)$A

gdiv <- diversity(A, factors = factors)

#walktrap factors
wdiv <- diversity(A, factors = "walktrap")
# }