NetworkToolbox: leverage – R documentation

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leverage

Leverage Centrality

Description

Computes leverage centrality of each node in a network (the degree of connected neighbors; Please see and cite Joyce et al., 2010)

Usage

leverage(A, weighted = TRUE)

Arguments

`A`	An adjacency matrix of network data
`weighted`	Is the network weighted? Defaults to `TRUE`. Set to `FALSE` for unweighted measure of leverage centrality

Value

A vector of leverage centrality values for each node in the network

Author(s)

Alexander Christensen <alexpaulchristensen@gmail.com>

References

Joyce, K. E., Laurienti, P. J., Burdette, J. H., & Hayasaka, S. (2010). A new measure of centrality for brain networks. PLoS One, 5 e12200.

Examples

# Pearson's correlation only for CRAN checks
A <- TMFG(neoOpen, normal = FALSE)$A

#Weighted
levW <- leverage(A)

#Unweighted
levU <- leverage(A, weighted = FALSE)

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