https://github.com/cran/RandomFields
Tip revision: fab3d29ef16569604858ee648b9e1f6f7d4a7c96 authored by Martin Schlather on 21 September 2014, 00:00:00 UTC
version 3.0.42
version 3.0.42
Tip revision: fab3d29
RR.Rd
\name{Distribution Families}
\alias{RR}
\alias{RRmodel}
\alias{RRmodels}
\title{
Distribution families (RR commands)
}
\description{
Distribution families to specify random parameters in the model definition.
}
\note{
The allowance of random parameters is a very recent, developing
feature of \pkg{RandomField}.
Future changings of the behaviour are not unlikely.
}
\details{
When simulating Gaussian random fields, the random parameters
are drawn only once at the very beginning.
So, if the argument \code{n} in \command{\link{RFsimulate}}
is greater than \code{1} then \code{n} simulations conditional
on a single realisation of the random parameters are
performed. See the examples below.
There are (simple) multivariate version and additional version to the
distributions families implemented. Further, \bold{any} distribution
family defined in R can be used, see the examples below
These function will allow for Baysian modelling. (Future project).
}
\section{Implemented models}{
\tabular{ll}{
\command{\link{RRdeterm}} \tab no scattering
\cr
\command{\link{RRdistr}} \tab families of distributions transferred
from R
\cr
\command{\link{RRgauss}} \tab a (multivariate) Gaussian random variable
\cr
\command{\link{RRloc}} \tab modification of location and scale
\cr
\command{\link{RRspheric}} \tab random scale for
the \command{\link{RMball}} to simulate \command{\link{RMspheric}}, etc.
%on lower
% dimensions by \command{\link{RPcoins}} and \command{\link{RPpoisson}}
\cr
\command{\link{RRunif}} \tab a (multivariate) uniform random variable
\cr
}
}
\note{
A further random element is \command{\link{RMsign}}, which is an
operator on shape functions. As an exception its name starts with
\code{RM} and not with \code{RR}.
}
\author{
Martin Schlather, \email{schlather@math.uni-mannheim.de}
\url{http://ms.math.uni-mannheim.de/de/publications/software
}
}
\seealso{
\link{RC},
\link{RF},
\link{RM},
\link{RP},
\command{\link{Other models}},
\command{\link{RFdistr}},
\code{\link[=RMmodelgenerator-class]{RMmodelgenerator}},
}
\keyword{spatial}
\keyword{distribution}
\examples{
RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
## RFoptions(seed=NA) to make them all random again
## here, the scale is given by an exponential variable:
model <- RMgauss(scale=exp())
for (i in 1:4) {
RFoptions(seed = i)
# each leads to a simulation with a different scale parameter
plot(model) ## random
plot(RFsimulate(model, x=seq(0,10,0.1)))
readline("press return")
}
# but here, all 4 simulations have same (but random) scale:
plot(RFsimulate(model, x=seq(0,10,0.1), n=4))
## hierarchical models are also possible:
## here, the scale is given by an exponential variable whose
## rate is given by a uniform variable
model <- RMgauss(scale=exp(rate=unif()))
plot(model)
plot(RFsimulate(model, x=seq(0,10,0.1)))
## HOWEVER, the next model is deterministic with scale \eqn{e=2.718282}.
model <- RMgauss(scale=exp(1))
plot(model)
plot(RFsimulate(model, x=seq(0,10,0.1)))
\dontshow{FinalizeExample()}
}