NetworkToolbox: participation – R documentation

Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!

participation

Participation Coefficient

Description

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.

Usage

participation(A, comm = c("walktrap", "louvain"))

Arguments

`A`	Network adjacency matrix
`comm`	A vector of corresponding to each item's community. Defaults to `"walktrap"` for the `cluster_walktrap` community detection algorithm. Set to `"louvain"` for the `louvain` community detection algorithm. Can also be set to user-specified communities (see examples)

Details

Values closer to 1 suggest greater within-community connectivity and values closer to 0 suggest greater between-community connectivity

Value

Returns a list containing:

`overall`	Participation coefficient without signs considered
`positive`	Participation coefficient with only positive sign
`negative`	Participation coefficient with only negative sign

Author(s)

Alexander Christensen <alexpaulchristensen@gmail.com>

References

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.

Examples

#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")

NetworkToolbox

Methods and Measures for Brain, Cognitive, and Psychometric Network Analysis

v1.4.1

GPL (>= 3.0)

Authors

Alexander Christensen [aut, cre] (<https://orcid.org/0000-0002-9798-7037>), Guido Previde Massara [ctb] (<https://orcid.org/0000-0003-0502-2789>)

Initial release

2020-12-07