https://github.com/cran/BDgraph
Tip revision: 72b95efce3f7c808386f6e86b3789d004a213bf5 authored by Reza Mohammadi on 25 December 2022, 06:20:14 UTC
version 2.72
version 2.72
Tip revision: 72b95ef
graph.sim.Rd
\name{graph.sim}
\alias{graph.sim}
\title{ Graph simulation }
\description{
Simulating undirected graph structures, including
"\code{random}", "\code{cluster}", "\code{scale-free}", "\code{lattice}", "\code{hub}", "\code{star}", and "\code{circle}".
}
\usage{
graph.sim( p = 10, graph = "random", prob = 0.2, size = NULL, class = NULL, vis = FALSE,
rewire = 0.05 )
}
\arguments{
\item{p}{number of variables (nodes).}
\item{graph}{ undirected graph with options
"\code{random}", "\code{cluster}", "\code{smallworld}", "\code{scale-free}", "\code{lattice}", "\code{hub}", "\code{star}", and "\code{circle}".
It also could be an adjacency matrix corresponding to a graph structure (an upper triangular matrix in which
\eqn{g_{ij}=1} if there is a link between notes \eqn{i} and \eqn{j}, otherwise \eqn{g_{ij}=0}).
}
\item{prob}{ if \code{graph} = "\code{random}", it is the probability that a pair of nodes has a link.}
\item{size}{number of links in the true graph (graph size).}
\item{class}{ if \code{graph} = "\code{cluster}", it is the number of classes. }
\item{vis}{visualize the true graph structure.}
\item{rewire}{rewiring probability for smallworld network. Must be between 0 and 1.}
}
\value{ The adjacency matrix corresponding to the simulated graph structure, as an object with \code{S3} class \code{"graph"}.}
\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} and Alexander Christensen }
\seealso{ \code{\link{bdgraph.sim}}, \code{\link{bdgraph}}, \code{\link{bdgraph.mpl}} }
\examples{
# Generating a 'hub' graph
adj <- graph.sim( p = 8, graph = "scale-free" )
plot( adj )
adj
}
\keyword{ simulation }
\keyword{graphs}