leverage: Leverage Centrality

In AlexChristensen/NetworkToolbox: Methods and Measures for Brain, Cognitive, and Psychometric Network Analysis

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 <[e-mail]>

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)

AlexChristensen/NetworkToolbox documentation built on March 6, 2023, 5:08 p.m.