https://github.com/cran/RandomFields
Tip revision: e10243fbd4eb0cbeaf518e67fbc5b8ad44889954 authored by Martin Schlather on 12 December 2019, 13:40:13 UTC
version 3.3.7
version 3.3.7
Tip revision: e10243f
RPdirect.Rd
\name{Square root}
\alias{Direct}
\alias{RPdirect}
\title{Methods relying on square roots of the covariance matrix}
\description{
Methods relying on square roots of the covariance matrix
}
\usage{
RPdirect(phi, boxcox)
}
\arguments{
\item{phi}{object of class \code{\link[=RMmodel-class]{RMmodel}};
specifies the covariance model to be simulated.}
\item{boxcox}{the one or two parameters of the box cox transformation.
If not given, the globally defined parameters are used.
See \command{\link{RFboxcox}} for details.
}
}
\details{
\command{RPdirect}
is based on the well-known method for simulating
any multivariate Gaussian distribution, using the square root of the
covariance matrix. The method is pretty slow and limited to
about 12000 points, i.e. a 20x20x20 grid in three dimensions.
This implementation can use the Cholesky decomposition and
the singular value decomposition.
It allows for arbitrary points and arbitrary grids.
}
\value{
\command{\link{RPdirect}} returns an object of class \code{\link[=RMmodel-class]{RMmodel}}.
}
\references{
\itemize{
\item
Schlather, M. (1999) \emph{An introduction to positive definite
functions and to unconditional simulation of random fields.}
Technical report ST 99-10, Dept. of Maths and Statistics,
Lancaster University.
}}
\me
\seealso{ \link{Gaussian},
\link{RP}, \link{RPsequential}.
}
\keyword{methods}
\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 <- RMgauss(var=10, s=10) + RMnugget(var=0.01)
plot(model, xlim=c(-25, 25))
z <- RFsimulate(model=RPdirect(model), 0:10, 0:10, n=4)
plot(z)
\dontshow{FinalizeExample()}}