\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 funtion that generates an objects of class \command{\link[=RMmodel-class]{RMmodel}} } \item{\code{type}:}{character string; specifies the cathegory 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{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 fiels 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 = "RMmodel")}: returns the structure of \code{x}} \item{print}{\code{signature(x = "RMmodel")}: identical with \command{show}-method} \item{[}{\code{signature(x = "RMmodelgenerator")}: enables accessing the slots via the "["-operator, e.g. x["maxdim"]} \item{[<-}{\code{signature(x = "RMmodelgenerator")}: 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 distribtion, 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., an non-stationary convariance function} \item{\code{'framework dependent'}:}{domain depends on the calling model} \item{\code{'mismatch'}:}{this option is used only internaly 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{''}:}{this option is used only internaly 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 cathegories; either the function is not monotone or properties are not known} \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{vdim=-1} means that the actual maxdim depends on the parameters; \code{vdim=-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 \email{malinows@math.uni-goettingen.de}; Martin Schlather, \email{schlather@math.uni-mannheim.de} \url{http://ms.math.uni-mannheim.de/de/publications/software}} \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}} } \examples{ RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set ## RFoptions(seed=NA) to make them all random again RFgetModelNames(group="type") \dontshow{FinalizeExample()} } \keyword{classes} \keyword{hplot}