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\name{rmvnorm}
\alias{rmvnorm}
\title{ Generate data from the multivariate Normal distribution }
\description{
Random generation function from the multivariate Normal distribution with mean equal to \eqn{mean} and covariance matrix \eqn{sigma}.
}
\usage{
rmvnorm( n = 10, mean = rep( 0, length = ncol( sigma ) ),
sigma = diag( length( mean ) ) )
}
\arguments{
\item{n}{ Number of observations. }
\item{mean}{ Mean vector, default is \eqn{rep( 0, length = ncol( sigma ) )}. }
\item{sigma}{ positive definite covariance matrix, default is \eqn{ diag( length( mean ) ) }. }
}
\value{ A numeric matrix with rows equal to \eqn{n} and columns equal to \eqn{length( mean )}. }
\author{ Reza Mohammadi \email{a.mohammadi@uva.nl} }
\seealso{\code{\link{bdgraph.sim}}, \code{\link{rwish}}, \code{\link{rgwish}} }
\examples{
mean <- c( 5, 20 )
sigma <- matrix( c( 4, 2,
2, 5 ), 2, 2 ) # covariance matrix
sample <- rmvnorm( n = 500, mean = mean, sigma = sigma )
plot( sample )
}
\keyword{ distribution }
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