degree: Degree

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

Degree

Description

Computes degree of each node in a network

Usage

degree(A)

Arguments

A	An adjacency matrix of network data

Value

A vector of degree values for each node in the network.

If directed network, returns a list containing:

inDegree	Degree of incoming edges (pointing to the node)
outDegree	Degree of outgoing edges (pointing away from the node)
relInf	Relative degree of incoming and outgoing edges. Positive values indicate more outgoing degree relative to incoming degree. Negative values indicate more incoming degree relative to outgoing degree

Author(s)

Alexander Christensen <[e-mail]>

References

Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: Uses and interpretations. NeuroImage, 52, 1059-1069.

Examples

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

deg <- degree(A)

#Directed network
## Not run: 
dep <- depend(neoOpen)

Adep <- TMFG(dep, depend = TRUE)$A

deg <- degree(Adep)

## End(Not run)

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