PCIT (version 1.5-3)

localClusteringCoefficient: Calculate the local clustering coefficient

Description

Calculate the local clustering coefficient for each node in an adjacency matrix. The clustering coefficient is defined as the proportion of existing connections from the total possible (Watts and Strogatz, 1998).

Usage

localClusteringCoefficient(adj)

Arguments

adj

- An adjacency matrix. Calculating the clustering coefficient only makes sense if some connections are zero i.e. no connection.

Value

A vector of local clustering coefficients for each node/gene of the adjacency matrix.

References

D.J. Watts and S.H. Strogatz. (1998) Collective dynamics of 'small-world' networks. Nature. 393(6684). 440-442.

See Also

clusteringCoefficient

Examples

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