leverage: Leverage Centrality

Description Usage Arguments Value Author(s) References Examples

Description

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

Usage

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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

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

#Weighted
levW <- leverage(A)

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

NetworkToolbox documentation built on May 28, 2021, 5:11 p.m.