Revision 68994912262e9c2ae98bff7968c23cd4cc8b9e8b authored by Martin Schlather on 24 August 2008, 00:00 UTC, committed by Gabor Csardi on 24 August 2008, 00:00 UTC
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\title{Internal functions -- do not use them directly}
  \code{CheckXT} checks whether the coordinates of the data and related
  parameters are specified correctly and transforms the coordinates into
  a standard format

  \code{PrepareModel} checks whether the parameters of the covariance
  model and related parameters are specified correctly and transforms
  the parameters into a standard format

  \code{} is the inverse function to
  \code{PrepareModel}; see Details

  \code{plotWithCircles} displays data values of marked point processes
  by circles

  \code{GetDistributionNames} returns the names of the currently
  available marginal distributions of the random fields

  \code{paramextract} extracts for some models some parameters
  from an internal parameter list

CheckXT(x, y, z, T, grid, gridtriple)
PrepareModel(model, param, timespacedim, trend, method=NULL,
             named=FALSE), allowed=c("standard", "nested", "list")) 
plotWithCircles(data, factor=1.0, xlim=range(data[,1])+c(-maxr,maxr),
                ylim=range(data[,2])+c(-maxr,maxr),col=1, fill=0, ...)
paramextract(p, model=c("cutoff"))
  \item{x}{\code{x} coordinates}
  \item{y}{\code{y} coordinates}
  \item{z}{\code{z} coordinates}
  \item{T}{time instances}
  \item{grid}{see \command{\link{GaussRF}}}
  \item{gridtriple}{see \command{\link{GaussRF}}}
  \item{model}{see \command{\link{GaussRF}}}
  \item{param}{see \command{\link{GaussRF}}}
  \item{timespacedim}{dimension of the random field including the time
    dimension, if there is any}
  \item{trend}{mean or trend of the random field}
  \item{method}{simulation method}
  \item{named}{logical. If \code{TRUE} \code{covnr} and \code{param}
    are returned with names}
  \item{l}{list as returned by \code{PrepareModel}}
  \item{allowed}{allowed output formats, see
  \item{data}{matrix of 3 columns; first two columns give the
    coordinates, the third the data}
  \item{factor}{enlargement factor for data}
  \item{xlim}{see \command{\link[graphics]{plot}}}
  \item{ylim}{see \command{\link[graphics]{plot}}}
  \item{col}{border colour of circles}
  \item{fill}{filling colour of circles}
  \item{...}{further graphical parameters}
  \item{p}{internal parameter list; e.g. the columns of
  \item{model}{the name of a covariance model.}
  \code{} is roughly speaking the inverse function to
  \code{PrepareModel}.  \code{} also tries to 
  simplify the model definition, but cannot rediscover the given method for
  the simulation of the nugget effect in all cases.  Due to the
  simplification in \code{} and the special
  definition of the nugget effect for nested models,
  \code{} may return a correct model definition in case
  of incorrect input, namely if \code{scale} is set to \eqn{0} in a list
  definition, see Examples.
%  lists of internal parameters
\author{Martin Schlather, \email{}
\keyword{ spatial }%-- one or more ...
% library(RandomFields)

x <- function(...) {
model <- list(list(model="whi", kappa=5, var=2, s=4), "+",
    list(model="whi", kappa=1, var=3, s=0)) ## s=0 should not be used only in
##                             a model definition where the parameters are
##                             are given in a matrix, see the result
x(model=model, ti=1, me="ci")

## since performs a one-step simplification,
## iterative calls may further simplify the model
xx <-, ti=1, me="ci"))
x(model=xx$mo, pa=xx$pa, ti=1, me=xx$me)

## back to the matrix definition of nested models
str(, ti=1), allowed="nested"))

## back to the (correct) list definition
str(, ti=1), allowed="list"))

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