https://github.com/cran/RandomFields
Tip revision: 6eca414de4c835af2032db4cae6c05e9cc684529 authored by Martin Schlather on 23 April 2016, 15:04:07 UTC
version 3.1.11
version 3.1.11
Tip revision: 6eca414
RPopitz.Rd
\name{Extremal t}
\alias{RPopitz}
\alias{extremal t}
\alias{extremal t process}
\title{Extremal t process}
\description{
\command{RPopitz} defines an extremal t process.
}
\usage{
RPopitz(phi, xi, mu, s, alpha)
}
\arguments{
\item{phi}{an \command{\link{RMmodel}};
covariance model for a standardized
Gaussian random fields, or the field itself.
}
\item{xi,mu,s}{the extreme value index, the location parameter and the
scale parameter, respectively, of the generalized extreme value
distribution. See Details.
}
\item{alpha}{originally referred to the \eqn{\alpha}-Frechet marginal
distribution, see the original literature for details.
}
}
\details{
The argument \code{xi} is always a number, i.e. \eqn{\xi} is constant in
space. In contrast, \eqn{\mu} and \eqn{s} might be constant
numerical value or given a \code{\link{RMmodel}}, in particular by a
\code{\link{RMtrend}} model. The default values of \eqn{mu} and \eqn{s}
are \eqn{1} and \eqn{z\xi}, respectively.
}
\author{Martin Schlather, \email{schlather@math.uni-mannheim.de}
\url{http://ms.math.uni-mannheim.de/de/publications/software}
}
\references{
\itemize{
\item
Davison, A.C., Padoan, S., Ribatet, M. (2012).
Statistical modelling of spatial extremes.
\emph{Stat. Science} \bold{27}, 161-186.
\item
Opitz, T. (2012) A spectral construction of the extremal t process.
\emph{arxiv} \bold{1207.2296}.
}
}
\seealso{
\command{\link{RMmodel}},
\command{\link{RPgauss}},
\command{\link{maxstable}},
\command{\link{maxstableAdvanced}}
}
\keyword{spatial}
\examples{
RFoptions(seed=0, xi=0)
## seed=0: *ANY* simulation will have the random seed 0; set
## RFoptions(seed=NA) to make them all random again
## xi=0: any simulated max-staable random field has extreme value index 0
\dontshow{StartExample()}
x <- seq(0, 2, 0.01)
model <- RPopitz(RMgauss(), alpha=2)
z1 <- RFsimulate(model, x)
plot(z1, type="l")
\dontshow{FinalizeExample()}
}