clusteringCoefficient: Calculate the clustering coefficient

In PCIT: Partial Correlation Coefficient with Information Theory

Description

Calculate the clustering coefficient for an adjacency matrix. By default, the local clustering coefficient is calculated.

Usage

	clusteringCoefficient(adj, FUN='localClusteringCoefficient', ...)

Arguments

adj	- An adjacency matrix. Calculating the clustering coefficient only makes sense if some connections are zero i.e. no connection.
FUN	- The function for calculating the clustering coefficient.
...	- Arguments to pass to FUN

Value

The clustering coefficient(s) for the adjacency matrix.

Author(s)

Nathan S. Watson-Haigh

See Also

localClusteringCoefficient clusteringCoefficientPercent

Examples

	data(PCIT)
	m <- m[1:200,1:200]        # just use a small subset of the data
	result <- pcit(m)
	m[idx(result)] <- 0
	
	clusteringCoefficient(m)

PCIT documentation built on May 1, 2019, 8:10 p.m.