Returns the clustering coefficients of the vertices in a graph.
ccoeff(model=NULL,edges=NULL,p=NULL)
gRapHD
object.
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.
number of vertices. If NULL
, the p=max(edges)
.
A vector with length p
with the clustering coefficient of each vertex.
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)
# }
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