wto: Weighted Topological Overlap

In hfgolino/EGA: Exploratory Graph Analysis – a Framework for Estimating the Number of Dimensions in Multivariate Data using Network Psychometrics

Weighted Topological Overlap

Description

Computes weighted topological overlap following the Novick et al. (2009) definition

Usage

wto(network, signed = TRUE, diagonal.zero = TRUE)

Arguments

network	Symmetric matrix or data frame. A symmetric network
signed	Boolean (length = 1). Whether the signed version should be used. Defaults to TRUE. Use FALSE for absolute values
diagonal.zero	Boolean (length = 1). Whether diagonal of overlap matrix should be set to zero. Defaults to TRUE. Use FALSE to allow overlap of a node with itself

Value

A symmetric matrix of weighted topological overlap values between each pair of variables

References

Original formalization
Nowick, K., Gernat, T., Almaas, E., & Stubbs, L. (2009). Differences in human and chimpanzee gene expression patterns define an evolving network of transcription factors in brain. Proceedings of the National Academy of Sciences, 106, 22358-22363.

Examples

# Obtain network
network <- network.estimation(wmt2[,7:24], model = "glasso")

# Compute wTO
wto(network)

hfgolino/EGA documentation built on Nov. 11, 2024, 9:28 p.m.