1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
|
\name{sparsity}
\alias{sparsity}
\title{ Compute the sparsity of a graph }
\description{ Compute the sparsity of a graph/network or an object of calss \code{"graph"} from function \code{\link{graph.sim}} or an object of calss "\code{sim}" from function \code{\link{bdgraph.sim}}. }
\usage{ sparsity( adj ) }
\arguments{
\item{adj}{
adjacency matrix corresponding to a graph structure in which \eqn{a_{ij}=1} if there is a link between notes \eqn{i}{i} and \eqn{j}{j}, otherwise \eqn{a_{ij}=0}.
It can be an object with \code{S3} class \code{"graph"} from function \code{\link{graph.sim}}.
It can be an object with \code{S3} class "\code{sim}" from function \code{\link{bdgraph.sim}}.
}
}
\value{ value corresponding to the graph sparsity which is the proportion of the non-links (non-zero elements) in \code{adj}. }
\references{
Mohammadi, R. and Wit, E. C. (2019). \pkg{BDgraph}: An \code{R} Package for Bayesian Structure Learning in Graphical Models, \emph{Journal of Statistical Software}, 89(3):1-30, \doi{10.18637/jss.v089.i03}
}
\author{ Reza Mohammadi \email{a.mohammadi@uva.nl} }
\seealso{ \code{\link{graph.sim}}, \code{\link{adj2link}}, \code{\link{link2adj}} }
\examples{
# Generating a 'random' graph
adj <- graph.sim( p = 10, graph = "random", prob = 0.4, vis = TRUE )
sparsity( adj )
}
\keyword{graphs}
|
