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\name{RFfunction}
\alias{RF}
\alias{RFmodel}
\alias{RFmodels}
\alias{RFfunction}
\alias{RFfunctions}
\title{Evaluation operators (RF commands)}
\description{
Here, all the \command{RF_name_} commands are listed.
}
\section{Functionals of \code{\link{RMmodels}}}{
The user's \code{\link{RMmodel}} is supplemented internally by
operators that are tacitely assumed, e.g. \command{\link{RPgauss}}.
Further completions of the user's model determine what should be
done with the model, e.g. calculation of the covariance
(\command{\link{RFcov}}).
The following list gives those \code{RFfunctions} that have
an internal representation as completion to the user's model.
\tabular{ll}{
% \bold{User's function} \tab \bold{Internal task} \cr
\command{\link{RFcalc}} \tab performs some simple calculations
based on \command{\link{R.models}}
\cr
\command{\link{RFcov}} \tab assigns to a covariance model the
covariance values
at given locations
\cr
\command{\link{RFcovmatrix}} \tab assigns to a covariance model the
matrix of covariance values at given locations
\cr
% \command{\link{RFget}} \tab not implemented yet\cr
\command{\link{RFdistr}} \tab generic function
assigning to a distribution family various values of the
distribution % (density function, distribution function, quantile, random sample)
\cr
\command{\link{RFfctn}} \tab assigns to a model the
value of the function at given locations. In case of a covariance
model \command{\link{RFfctn}} is identical to \command{\link{RFcov}}.
\cr
\command{\link{RFlikelihood}} \tab assigns to a model and a dataset the
(log)likelihood value.
\cr
\command{\link{RFlinearpart}} \tab assigns to a model and a set of
coordinates the linear part of the model, i.e. the deterministic
trend and the design matrix.
\cr
\command{\link{RFpseudovariogram}} \tab assigns to a model the
values of the pseudo variogram
at given locations\cr
\command{\link{RFsimulate}} \tab assigns to a model
a realisation of the corresponding random field
\cr
\command{\link{RFvariogram}} \tab assigns to a model the
values of the (cross-)variogram
at given locations\cr
}
}
\section{Estimation and Inference}{
\tabular{ll}{
% \bold{User's function} \tab \bold{Description} \cr
\command{\link{RFcrossvalidate}} \tab cross validation for Gaussian fields
\cr
\command{\link{RFvariogram}} \tab
empirical variogram
\cr
\command{\link{RFfit}} \tab
(maximum likelihood) fitting of the parameters
\cr
\command{\link{RFinterpolate}} \tab \code{'kriging' and 'imputing'}
\cr
% \command{\link{RFlikelihood}} \tab not coded yet % to do \cr
\command{\link{RFratiotest}} \tab likelihood ratio test for Gaussian fields
\cr
}
}
\section{Graphics for Gaussian fields}{
\tabular{ll}{
\command{\link{RFgui}} \tab educational tool for\cr
\tab * manual selection of a covariance model\cr
\tab * manual fitting to the empirical variogram
\cr
\command{\link{RFfractaldim}} \tab
determination of the fractal dimension
\cr
\command{\link{RFhurst}} \tab
determination of the Hurst effect (long range dependence)
\cr
}
}
\section{Coordinate transformations}{
\tabular{ll}{
\command{\link{RFearth2cartesian}} \tab
transformation of earth coordinates to cartesian coordinates
\cr
\command{\link{RFearth2dist}} \tab transformation of earth
coordinates to Euclidean distances
}
}
\section{Information from and to RandomFields}{
\tabular{ll}{
\command{\link{RFgetMethodNames}} \tab
currently implemented list of simulation methods
\cr
\command{\link{RFgetModel}} \tab
returns the model used in a \code{\link{RFfunction}}, with some
more details
%on the implementation
% \cr\tab including the default values of the arguments of the model
\cr
\command{\link{RFgetModelInfo}} \tab
similar to \command{\link{RFgetModel}}, but with detailed
information on the implementation
\cr
\command{\link{RFgetModelNames}} \tab
lists the implemented models
\cr
\command{\link{RFoptions}} \tab
options of package RandomFields
}
}
\seealso{
\link{RC}, \link{RM}, \link{RP},
\link{RR}, \link{R.},
\code{\link[=RMmodelgenerator-class]{RMmodelgenerator}}
}
\me
\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
z <- RFsimulate(model=RMexp(), 1:10)
RFgetModel(RFsimulate, show.call = TRUE) # user's definition
RFgetModel(RFsimulate, show.call = FALSE) # main internal part
\dontshow{FinalizeExample()}}
|
