https://github.com/cran/sn
Tip revision: 81bbbd29235f6793a9dcb486e22ff32edf6cc58c authored by Adelchi Azzalini on 08 October 2007, 00:00:00 UTC
version 0.4-4
version 0.4-4
Tip revision: 81bbbd2
msn.marginal.Rd
\name{msn.marginal}
\alias{msn.marginal}
\title{
Marginal components of a multivariate skew-normal distribution
}
\description{
Computes the marginal distribution of a subset of components of a
multivariate skew-normal distribution.
}
\synopsis{
msn.marginal(xi=rep(0, length(alpha)), Omega, alpha, comp=1:d, dp=NULL)
}
\usage{
msn.marginal(xi, Omega, alpha, comp)
msn.marginal(dp=, comp)
}
\arguments{
\item{xi}{
a numeric vector of length \code{d}, say, giving the location parameter.
}
\item{Omega}{
a covariance matrix of dimension \code{(d,d)}.
}
\item{alpha}{
a numeric vector of length \code{d}, which regulates the shape of the density.
}
\item{comp}{
a vector containing a subset of \code{1:d} selecting the components of the
marginal distribution. A permutation of \code{1:d} is allowed, and
the components of \code{comp} do not need to be sorted.
}
\item{dp}{
a list containing the components \code{xi}, \code{Omega},
\code{alpha}, contaning quantities as described above; if \code{dp} is
specified, then the indicidual components must not be in the calling
statement
}}
\value{
A list containing components \code{xi, Omega, alpha} with the
parameters of the marginal distribution. If \code{length(comp)} is equal to
\code{m}, say, then the new components are of size \code{m, (m,m), n},
respectively.
}
\section{Background}{
See the reference below for background information.
}
\references{
Azzalini, A. and Capitanio, A. (1999).
Statistical applications of the multivariate skew-normal distribution.
\emph{J.Roy.Statist.Soc. B} \bold{61}, 579--602.
}
\seealso{
\code{\link{dmsn}}, \code{\link{msn.conditional}}, \code{\link{msn.affine}}
}
\examples{
xi <- c(10,0,-30)
Omega <- 5*diag(3)+outer(1:3,1:3)
alpha <- c(1,-3,5)
msn.marginal(xi,Omega,alpha,c(3,1))
msn.marginal(dp=list(xi=xi,Omega=Omega,alpha=alpha), comp=3)
}
\keyword{multivariate}
\keyword{distribution}