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\name{RMschur}
\alias{RMschur}
\title{Schur product}
\description{
The covariance function is
\deqn{C(x)= M * \phi(x)}
where \sQuote{*} denotes the Schur product, i.e. elementwise
multiplication.
}
\usage{
RMschur(phi, M, diag, rhored, var, scale, Aniso, proj)
}
\arguments{
\item{phi}{covariance function of class \code{\link[=RMmodel-class]{RMmodel}}}
\item{M}{constant \eqn{n \times n}{n x n} covariance matrix of the
same size as multivariate model \code{phi}}
\item{diag,rhored}{alternative way of passing \code{M}:
\code{diag} is a vector of variances, \code{rhored} is a vector
containing the correlations of the lower triangle of the \code{M}.
}
\item{var,scale,Aniso,proj}{optional arguments; same meaning for any
\command{\link{RMmodel}}. If not passed, the above
covariance function remains unmodified.}
}
\value{
\command{\link{RMschur}} returns an object of class \code{\link[=RMmodel-class]{RMmodel}}.
}
\references{
\itemize{
\item ?
}
}
\me
\seealso{
\command{\link{RMmodel}},
\command{\link{RMmatrix}}.
}
\keyword{spatial}
\keyword{models}
\examples{\dontshow{StartExample()}
RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
## RFoptions(seed=NA) to make them all random again
model <- RMschur(M=matrix(c(2, 1, 1, 1), ncol=2), RMparswm(nudiag=c(0.5, 2)))
plot(model)
x <- seq(0, 10, 0.02)
plot(RFsimulate(model, x=x))
\dontshow{FinalizeExample()}}
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