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\name{RMmodelgenerator-class}
\docType{class}
\alias{RMmodelgenerator-class}
\alias{show,RMmodelgenerator-method}
\alias{[,RMmodelgenerator-method}
\alias{[,RMmodelgenerator,ANY,ANY-method}
\alias{[,RMmodelgenerator,ANY,ANY,ANY-method}
\alias{[<-,RMmodelgenerator,ANY,ANY-method}
\alias{[<-,RMmodelgenerator,ANY,ANY,ANY-method}
\alias{[<-,RMmodelgenerator-method}
\alias{print.RMmodelgenerator}
\title{Class \code{RMmodelgenerator} }
\description{ Class for all functions of this package with prefix \code{RM},
i.e. all functions that generate objects of class
\code{\link[=RMmodel-class]{RMmodel}}; direct extension of
class \code{\link[methods:function-class]{function}}.
}
\section{Creating Objects}{
Objects should not be created by the user!
}
\section{Slots}{
\describe{
\item{\code{.Data}:}{function; the genuine function that generates an
object of class
\command{\link[=RMmodel-class]{RMmodel}} }
\item{\code{type}:}{character string; specifies the category of
RMmodel-function, see Details}
\item{\code{domain}:}{character string; specifies whether the
corresponding function(s) depend on 1 or 2 variables, see Details}
\item{\code{isotropy}:}{character string; specifies the type of
isotropy of the corresponding covariance model, see Details}
\item{\code{operator}:}{logical; specifies whether the underlying
covariance model is an operator, see Details}
\item{\code{monotone}:}{character string; specifies the kind of monotonicity
of the model}
\item{\code{finiterange}:}{logical; specifies whether the underlying
covariance model has finite range, see Details}
% finiterange waere wuenschenswert an Abhaengigkeit von parametern
% und submodellen anzupassen, siehe maxdim und vdim
\item{\code{simpleArguments}:}{logical. If \code{TRUE} than all the
parameters are real valued (or integer valued).
}
\item{\code{maxdim}:}{numeric; the maximal dimension, in which the
corresponding model is a valid covariance model, see Details}
\item{\code{vdim}:}{numeric; dimension of the value of the random
field at a single fixed location, equals 1 in most cases, see
Details}
}
}
\section{Extends}{
Class \code{\link[methods:function-class]{function}}, directly.
}
\section{Methods}{
\describe{
\item{show}{\code{signature(x = CLASS_CLIST)}: returns the structure
of \code{x}}
\item{print}{\code{signature(x = CLASS_CLIST)}: identical with
\command{show}-method}
\item{[}{\code{signature(x = CLASS_RM)}: enables accessing
the slots via the "["-operator, e.g. x["maxdim"]}
\item{[<-}{\code{signature(x = CLASS_RM)}: enables replacing
the slots via the "["-operator}
}
}
\section{Details}{
\describe{
\item{\code{type}:}{can be one of the following strings:
\describe{
\item{\code{'tail correlation function'}:}{
indicates that the function returns a
tail correlation function (a subclass of the set of
positive definite functions)
}
\item{\code{'positive definite'}:}{indicates that the function returns a
covariance function (positive definite function)}
\item{\code{'negative definite'}:}{indicates that the function returns a
variogram model (negative definite function)}
\item{\code{'process'}:}{functions of that type determine
the class of
processes to be simulated}
\item{\code{'method for Gauss processes'}:}{methods to simulate
Gaussian random fields}
\item{\code{'method for Brown-Resnick processes'}:}{methods to
simulate Brown-Resnick fields}
\item{\code{'point-shape function'}:}{functions of that type
determine the distribution of points in space}
\item{\code{'distribution family'}:}{
e.g. (multivariate) uniform distribution, normal distribution,
etc.,
defined in \pkg{RandomFields}.
See \link{RR} for a complete list.
}
\item{\code{'shape function'}:}{functions used in, e.g., M3 processes (\link{RPsmith})}
\item{\code{'trend'}:}{\link{RMtrend} or a \link[=RFformula]{mixed model} }
\item{\code{'interface'}:}{indicates internal models which are usually
not visible for the users. These functions are the internal
representations of \command{\link{RFsimulate}},
\command{\link{RFcov}}, etc. See \link{RF} for a complete list.
}%\item{\code{'undefinded'}:}{}
\item{\code{'undefined'}:}{some models can take different types,
depending on the parameter values and/or the submodels }
\item{\code{'other type'}:}{very very special internal functions,
not belonging to any of the above types.
}
}
}
\item{\code{domain}:}{can be one of the following strings:
\describe{
\item{\code{'single variable'}:}{Function depending on a single variable}
\item{\code{'kernel'}:}{model refers to a kernel, e.g. a non-stationary covariance function}
\item{\code{'framework dependent'}:}{domain depends on the calling model}
\item{\code{'mismatch'}:}{this option is used only internally and should never appear}
}
}
\item{\code{isotropy}:}{can be one of the following strings:
\describe{
\item{\code{'isotropic'}:}{indicates that the model is isotropic}
\item{\code{'space-isotropic'}:}{indicates that the spatial part of a
spatio-temporal model is isotropic}
\item{\code{'zero-space-isotropic'}:}{this property refers to space-time
models; the model is called zerospaceisotropic if it is
isotropic as soon as the time-component is zero}
\item{\code{'vector-isotropic'}:}{multivariate vector model (flow
fields) have a different notion of isotropy}
\item{\code{'symmetric'}:}{the most basic property of any
covariance function or variogram model}
\item{\code{'cartesian system'}, \code{'earth system'},
\code{'spherical system'}, \code{'cylinder system'}:}{
different coordinate systems
}
\item{\code{'non-dimension-reducing'}:}{the property \eqn{f(x)
= f(-x)^\top} does not hold
}
\item{\code{'parameter dependent'}:}{indicates that the type of
isotropy of the model depends on the parameters passed to the
model; in particular parameters may be submodels if an operator model
is considered}
\item{\code{'<mismatch>'}:}{this option is used only internally and should never appear}
}
}
\item{\code{operator}:}{if \code{TRUE}, the model requires at least
one submodel}
\item{\code{monotone}:}{
\describe{
\item{\code{'mismatch in monotonicity'}:}{used if a statement on
the monotonocity does not make sense, e.g. for
\code{\link{RRmodels}}
}
\item{\code{'submodel dependent monotonicity'}:}{only for operators,
e.g. \code{\link{RMS}}}
\item{\code{'previous model dependent monotonicity'}:}{internal;
should not be used}
\item{\code{'parameter dependent monotonicity'}:}{some models change
their properties according to the parameters}
\item{\code{'not monotone'}:}{none of the above categories; either
the function is not monotone or properties are unknown}
\item{\code{'monotone'}:}{isotone or antitone}
\item{\code{'Gneiting-Schaback class'}:}{function belonging to
Euclid's hat in Gneiting's 1999 paper}
\item{\code{'normal mixture'}:}{scale mixture of the Gaussian model}
\item{\code{'completely monotone'}:}{completely monotone function}
\item{\code{'Bernstein'}:}{Bernstein function}
}
Note that
\itemize{
\item \code{'not monotone'} includes \code{'monotone'}
and \code{'Bernstein'}
\item \code{'monotone'} includes \code{'Gneiting-Schaback class'}
\item \code{'Gneiting-Schaback class'} includes \code{'normal mixture'}
\item \code{'normal mixture'} includes \code{'completely monotone'}
}
}
\item{\code{finiterange}:}{if \code{TRUE}, the covariance of the
model has finite range}
\item{\code{maxdim}:}{if a positive integer, \code{maxdim} gives the
maximum dimension in which the model is a valid covariance model,
can be \code{Inf};
\code{maxdim=-1} means that the actual maxdim depends on the
parameters; \code{maxdim=-2} means that the actual maxdim depends on
the submodel(s)}
\item{\code{vdim}:}{if a positive integer, \code{vdim} gives the
dimension of the random field, i.e. univariate, bi-variate, ...;
\code{vdim=-1} means that the actual vdim depends on the
parameters; \code{vdim=-2} means that the actual vdim depends on
the submodel(s)}
}
}
\author{Alexander Malinowski, \martin}
\references{
\itemize{
\item Gneiting, T. (1999) Radial positive definite functions
generated by Euclid's hat, \emph{J. Multivariate Anal.},
\bold{69}, 88-119.
}
}
\seealso{
\code{\link[=RMmodel-class]{RMmodel}},
\code{\link{RFgetModelNames}}
}
\keyword{classes}
\keyword{hplot}
\examples{\dontshow{StartExample()}
RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
## RFoptions(seed=NA) to make them all random again
RFgetModelNames()
\dontshow{FinalizeExample()}}
|
