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\name{RPt}
\alias{RPt}
\title{Simulation of T Random Fields}
\description{
\command{RPt} defines a t field.
}
\usage{
RPt(phi, boxcox, nu)
}
\arguments{
\item{phi}{the \command{\link{RMmodel}}. If a model for the
distribution is not specified, \command{\link{RPgauss}} is used as
default and a covariance model is expected.}
\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.
}
\item{nu}{non-negative number. Degree of freedom.}
}
\value{
The function returns an object of class \code{\link[=RMmodel]{RMmodel}}.
}
\me
\seealso{
\command{\link{Auxiliary RMmodels}},
\command{\link{RP}},
\command{\link{RPgauss}}.
}
\references{
Related to the extremal t process
\itemize{
\item
T. Opitz (2012) A spectral construction of the extremal t process.
\emph{arxiv} \bold{1207.2296}.
}
}
\keyword{spatial}
\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 <- RPt(RMexp(), nu=2)
x <- seq(0, 10, 0.1)
z <- RFsimulate(model, x, x, n=4)
plot(z)
\dontshow{FinalizeExample()}}
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