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).
Value
A vector with length p with the clustering coefficient of each vertex.
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.
# NOT RUN {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)
# }