ccoeff: Clustering coefficient

In gRapHD: Efficient Selection of Undirected Graphical Models for High-Dimensional Datasets

Description

Returns the clustering coefficients of the vertices in a graph.

Usage

ccoeff(model=NULL,edges=NULL,p=NULL)

Arguments

model	gRapHD object.
edges	matrix with 2 columns, each row representing one edge, and each column one of the vertices in the edge. Column 1 contains the vertex with lower index.
p	number of vertices. If NULL, the p=max(edges).

Details

The clustering coefficient is given by C_i=2*e_i/(k_i*(k_i-1)), where k_i is the number of neighbours the vertex i has, and e_i is the number of edges between the neighbours of i.

Value

A vector with length p with the clustering coefficient of each vertex.

Author(s)

Gabriel Coelho Goncalves de Abreu ([e-mail])

Examples

data(dsCont)
m <- minForest(dsCont,homog=TRUE,forbEdges=NULL,stat="BIC")
m1 <- stepw(m,dsCont)
cc <- ccoeff(edges=m1@edges,p=m1@p)
mean(cc)

gRapHD documentation built on Feb. 9, 2018, 6:05 a.m.