\name{RFparameters}
\alias{RFparameters}
\title{Control Parameters}
\description{
\code{RFparameters} sets and returns control parameters for the simulation
of random fields
}
\usage{
RFparameters(..., no.readonly=FALSE)
}
\arguments{
\item{...}{arguments in \code{tag = value} form, or a list of tagged
values.}
\item{no.readonly}{If \command{RFparameters} is called without
parameter then all parameters are returned in a list. If
\code{no.readonly=TRUE} then only rewritable parameters are returned.
}
}
\details{
The possible parameters are
%
\cr\cr\bold{General options}\cr
\describe{
\item{\code{PracticalRange}}{logical or 2, 3, 11, 12, 13.
If not \code{FALSE} the range of the covariance functions is
adjusted so that cov(1) is about 0.05 (for \code{scale==1}).
\itemize{
\item \code{FALSE} : the practical range ajustment is not used.
\item \code{TRUE} : \code{PracticalRange} is applicable only if the value
is known exactly.
\item \code{2} : \code{PracticalRange} is applicable if the value is
known pretty well
\item \code{3} : \code{PracticalRange} is applicable if the value is
roughly known
\item \code{11} : if the practical range is not known exactly it
is approximated numerically.
\item \code{12} : if the practical range is not known pretty well it
is approximated numerically.
\item \code{13} : if the practical range is even not known
approximately it is approximated numerically.
}
Note that values beyond \code{FALSE}, \code{TRUE}, and \code{11},
are only used for specialists' purposes.
Default: \code{FALSE} [init].}
\item{\code{PrintLevel}}{If \code{PrintLevel}\eqn{\le0}{<=0}
there is not any output on the screen. The
higher the number the more tracing information is given.
Default: 1 [init, do].\cr
1 : error messages\cr
2 : messages about partial failures of the algorithm\cr
>2 : additional informations
Note that \code{PrintLevel} is also used in other packages
as a default, for example in \link[SoPhy]{SoPhy}
(\command{\link[SoPhy]{risk.index}} and
\command{\link[SoPhy]{create.roots}}). The changing of
\code{PrintLevel} here may cause some unexpected effects in these
functions. See the documentation there.
}
}
%
\bold{General options for simulating}\cr
\describe{
\item{\code{pch}}{Character or empty string.
The character is printed after each
performed simulation if more than one simulation is performed at
once. If \code{pch='!'} then a counter is shown instead of the character.
Note that also '\eqn{\mbox{\textasciicircum}}{^}H's are printed if
the counter (\code{pch='!'}) is shown,
which may have undesirable interactions with some few other R
functions, e.g. \command{\link[utils]{Sweave}}.
Default: \code{'*'} [do].
}
\item{\code{Storing}}{Logical.
If \code{TRUE} then intermediate results are kept
after each simulation; if several simulation are performed with the same
model parameters then
\code{Storing=TRUE} accelerates the simulations, but needs additional
memory. \cr
Note that in subsequent calls of \code{\link{GaussRF}}
intermediate changes of RFparameters with flag "[init]"
do not have any influence on the algorithm.
Hence, for studying the effects for
divers values of technical parameters like
\code{CE.force}, \code{CE.mmin}, etc. the parameter \code{Storing} must be
\code{FALSE}. See also last paragraphs in the Details.
Default: \code{TRUE} [init, do].
}
\item{\code{stationary.only}}{Logical or NA. Used for the automatic
choice of methods. See also \link{RFMethods}.
\itemize{
\item \code{TRUE}: the simulation of non-stationary random
fields is refused. In particular, the intrinsic
embedding method is excluded and
the simulation of Brownian motion is rejected.
\item \code{FALSE}: intrinsic embedding is always allowed,
actually it's the first one considered in the automatic
selection algorithm.
\item \code{NA}: the simulation of the Brownian motion allowed,
but intrinsic embedding is not used for stationary random fields.
}
Default: \code{NA} [init].}
}
%
\bold{Options for simulating with the circulant embedding method}\cr
\describe{
\item{\code{CE.force}}{Logical. Circulant embedding does not work if a
certain matrix has negative eigenvalues. Sometimes it is convenient
to replace all the negative eigenvalues by zero
(\code{CE.force==TRUE}) after \code{CE.trials} number of trials.
Default: \code{FALSE} [init].
}
\item{\code{CE.mmin}}{Scalar or vector.
Circulant embedding usually uses the smallest matrix
possible; by \code{CE.mmin} the minimum number of rows and columns
of the matrix are given. If \code{CE.mmin>=0} then the minimum
absolute size is given.\cr
If \code{CE.mmin<0} then the follow holds.
If \code{CE.userfft==FALSE} then the matrix
has \code{-CE.mmin} times the size of the size of the smallest
matrix. If \code{CE.userfft==TRUE} then the matrix
has \code{max(-CE.mmin/2,1)} times the size of the size of the smallest
matrix. Default: \code{0} [init].}
\item{\code{CE.strategy}}{0 : if matrix has negative eigenvalues then the
size in each direction is doubled; \cr 1 : the size is enhanced only in
one direction, namely that where the covariance function has the
largest value at the end point of the grid - note that
the default value of \code{CE.trials} is probably too small
in that case. \cr Default: \code{0}
[init].}
\item{\code{CE.maxmem}}{maximum edge length of the ciculant matrix;
the total amount of memory needed for internal calculation
is about 16 (=2 * sizeof(double))
times as large if \code{\link{RFparameters}()$Storing=FALSE}
and 32 (=4 * sizeof(double)) time as large if \code{Storing=TUE}
\cr Default: \code{20000000} [init].
}
\item{\code{CE.tolIm}}{Circulant embedding.
If the modulus of the imaginary part is less than
\code{CE.tolIm} then the eigenvalue is considered as real.
Default: \code{1E-3} [init].}
\item{\code{CE.tolRe}}{Circulant embedding.
Threshold above which eigenvalues are considered as
non-negative. Default: \code{-1E-5} [init].}
\item{\code{CE.trials}}{Circulant embedding.
A larger embedding matrix is likely to make more eigenvalues
non-negative. If at least one of the thresholds \code{CE.tolRe} and
\code{CE.tolIm} are missed then the matrix size is doubled,
and the matrix is checked again. This procedure is repeated
up to \code{CE.trials-1} times. If there are still negative
eigenvalues, the simulation method fails if \code{CE.force==FALSE}.
Default: \code{3} [init].
}
\item{\code{CE.userfft}}{Logical. If \code{FALSE}
the columns of the circulant matrix
have length \eqn{2^k} for some \eqn{k}. Otherwise the algorithm
tries to find a nicely factorizable number close to the size of the
given matrix. Default: \code{FALSE} [init].}
}
%
\bold{Options for simulating with the local circulant embedding methods}\cr
\describe{
\item{\code{cutoff.a}}{Cut-off embedding.
The key parameter in the local covariance functions. If
\code{cutoff.a==0} then the simulation method will assign
an appropriate value to it for each local covariance function;
If \code{cutoff.a>0} then the simulation method will use this
value for every local covariance function.
Default: \code{0} [init].
}
\item{\code{intrinsic.r}}{Intrinsic embedding.
The key parameter in the local covariance functions. If
\code{intrinsic.r==0} then the simulation method will assign
an appropriate value to it for each local covariance function;
If \code{intrinsic.r>0} then the simulation method will use this
value for every local covariance function.
Default: \code{0} [init].
}
}
\bold{Options for simulating by simple matrix decomposition}\cr
\describe{
\item{\code{direct.checkprecision}}{Gaussian
random vectors can be generated
by means of the square root of the covariance matrix.
By default Cholesky decomposition is used. If
\code{direct.checkprecision==TRUE} then the precision is checked.
Default: \code{FALSE} [init].}
\item{\code{direct.maxvariables}}{Decomposition of the covariance matrix.
If the number of variables to generate is
greater than \code{direct.maxvariables}, then any matrix decomposition
method is rejected. It is important that this option is set
conveniently if \code{method==NULL} in \link{GaussRF}.
Default: \code{1800} [init]}
\item{\code{direct.method}}{Decomposition of the covariance matrix.
If \code{direct.method==1}, Cholesky
decomposition will not be attempted, but singular value
decomposition
used instead.
Default: \code{0} [init].}
\item{\code{direct.requiredprecision}}{Decomposition of the covariance
matrix.
If \code{direct.checkprecision==TRUE} and
the \code{direct.requiredprecision} is not reached then Cholesky
decomposition fails, and singular value decomposition is used.
Default: \code{1e-11} [init].
}
}
%
\bold{Options for simulating with a turning bands method}\cr
\describe{
\item{\code{spectral.grid}}{Logical. Spectral turning bands is implemented
for 2 dimensions only. The angle of the lines is random if
\code{spectral.grid==FALSE},
and \eqn{k\pi/}{k*pi/}\code{spectral.lines}
for \eqn{k}{k} in \code{1:spectral.lines},
otherwise. Default: \code{TRUE} [do].}
\item{\code{spectral.lines}}{Spectral turning bands.
Number of lines used (in total for all additive components of the
covariance function). Default: \code{500} [do].}
%\item{\code{TBM.method}}{Set at init time; setting ignored and stored
%setting used if other parameters are identical to former parameters!
%-- use DeleteKey, to make sure that the current setting is used.
% [init]}
\item{\code{TBM.method}}{character.
Currently either \code{'circulant embedding'} or \code{'direct'}.
The preferred method to simulate on the line. If \code{'direct'}
then the method is overwritten if the number of points on the grid
is larger than \code{direct.maxvariables}.
}
\item{\code{TBM2.every}}{If \code{TBM2.every>0} then every
\code{TBM2.every}th iteration is announced.
Default: \code{0} [do].}
\item{\code{TBM2.lines}}{Ordinary 2-dimensional turning bands method.
Number of lines used.
Default: \code{60} [do].}
\item{\code{TBM2.linesimufactor}}{Either \code{TBM2.linesimufactor} or
\code{TBM2.linesimustep} must be greater than zero. The parameter
that is zero is ignored. The grid on the line is
\code{TBM2.linesimufactor}-times
finer than the smallest distance.
See also \code{TBM2.linesimustep}.
Default: \code{2.0} [init].}
\item{\code{TBM2.linesimustep}}{
If \code{TBM2.linesimustep} is positive the grid on the line has lag
\code{TBM2.linesimustep}.
See also \code{TBM2.linesimufactor}.
Default: \code{0.0} [init].}
\item{\code{TBM2.num}}{
Logical. If \code{TRUE} then the covariance function on the line
for the two-dimensional simulation is approximated numerically.
If \code{FALSE} only those models are allowed for the
2-dimensional simulation that have an analytic representation on
the line.
Default: \code{FALSE} [init].}
\item{\code{TBM3D2.every}}{If \code{TBM3D2.every>0} then every
\code{TBM3D2.every}th iteration is announced.
Default: \code{0} [do].}
\item{\code{TBM3D2.lines}}{Ordinary 3-dimensional turning bands method,
simulation of a \emph{2-dimensional} field.
Number of lines used.
Default: \code{500} [do].}
\item{\code{TBM3D2.linesimufactor}}{Either \code{TBM3D2.linesimufactor} or
\code{TBM2.linesimustep} must be greater than zero. The parameter
that is zero is ignored. The grid on the line is
\code{TBM3D2.linesimufactor}-times
smaller than the smallest distance. See also \code{TBM3D2.linesimustep}.
Default: \code{2.0} [init].}
\item{\code{TBM3D2.linesimustep}}{The grid on the line has lag
\code{TBM3D2.linesimustep}. See also \code{TBM3D2.linesimufactor}.
Default: \code{0.0} [init].}
\item{\code{TBM3D3.every}}{If \code{TBM3D3.every>0} then every
\code{TBM3D3.every}th iteration is announced.
Default: \code{0} [do].}
\item{\code{TBM3D3.lines}}{Ordinary 3-dimensional turning bands method,
simulation of a \emph{3-dimensional field}.
Number of lines used.
Default: \code{500} [do].}
\item{\code{TBM3D3.linesimufactor}}{Either \code{TBM3D3.linesimufactor} or
\code{TBM2.linesimustep} must be greater than zero. The parameter
that is zero is ignored. The grid on the line is
\code{TBM3D3.linesimufactor}-times smaller than the smallest
distance. See also \code{TBM3D3.linesimustep}.
Default: \code{2.0} [init].}
\item{\code{TBM3D3.linesimustep}}{The grid on the line has lag
\code{TBM3D3.linesimustep}. See also \code{TBM3D3.linesimufactor}.
Default: \code{0.0} [init].}
\item{\code{TBMCE.force}}{Ordinary TBM methods. This
parameter corresponds to \code{CE.force} and is used when
simulating with circulant embedding on line.
Default: \code{FALSE} [init].}
\item{\code{TBMCE.mmin}}{Ordinary TBM methods. This parameter corresponds to
\code{CE.mmin}. Default: \code{0} [init].}
\item{\code{TBMCE.strategy}}{Ordinary TBM methods. This parameter
corresponds to \code{CE.strategy}. Default: \code{0} [init].}
\item{\code{TBMCE.maxmem}}{Ordinary TBM methods. This parameter
corresponds to \code{CE.maxmem}. Default: \code{20000000} [init].}
\item{\code{TBMCE.tolIm}}{Ordinary TBM methods. This parameter corresponds
to \code{CE.tolIm}. Default: \code{1E-3} [init].}
\item{\code{TBMCE.tolRe}}{Ordinary TBM methods. This parameter corresponds
to \code{CE.tolRe}. Default: \code{-1E-5} [init].}
\item{\code{TBMCE.trials}}{Ordinary TBM methods. This parameter corresponds
to \code{CE.trials}. Default: \code{3} [init].}
\item{\code{TBMCE.userfft}}{Ordinary TBM methods. This parameter corresponds
to \code{CE.userfft}. Default: \code{true} [init].}
}
%
\bold{Options for simulating with Poisson point processes}\cr
\describe{
\item{\code{add.MPP.realisations}}{Random coins.
Number of superposed
realisations (to approximate the normal distribution; total number
for all (additive) components with same anisotropy);
Default: \code{100} [do].}
\item{\code{MPP.approxzero}}{Marked point processes. Functions that
do not have
compact support are set to zero outside the ball outside which the
function has absolute values less than \code{MPP.approxzero}.
Default: \code{0.001} [init].}
\item{\code{MPP.radius}}{Marked point processes.
In order avoid edge effects, the simulation area is enlarged by
a constant \eqn{r}{r} so that all marks have their
(supposed) support in the ball with radius \eqn{r}{r} centred at
the origin; see also \code{MPP.approxzero}.
If \code{MPP.radius>0} the true radius \eqn{r}{r} is replaced by
\code{MPP.radius}.
Default: \code{0.0} [init].}
}
%
\bold{Options for simulating hyperplane tessellations}\cr
\describe{
\item{\code{hyper.superpos}}{integer.
number of superposed hyperplane tessellations.
Default: \code{100} [do].
}
\item{\code{hyper.maxlines}}{integer.
estimated number of maximal lines.
Default: \code{1000} [init].
}
\item{\code{hyper.mar.distr}}{integer.
code for the marginal distribution used in the
simulation:
\itemize{
\item{0}{uniform distribution}
\item{1}{Frechet distribution with form parameter
\code{hyper.mar.param}}
\item{2}{Bernoulli distribution (Binomial with \eqn{n=1}) with
parameter \code{hyper.mar.param}}
}
The parameter should not be changed yet.
Default: \code{0} [do].
}
\item{code{hyper.mar.param}}{Parameter used for the marginal
distribution.
Default: \code{NA} [do].
}
}
\bold{Options specific to simulating max-stable random fields}
\describe{
\item{\code{maxstable.maxGauss}}{Max-stable random fields.
The simulation of the max-stable process based on random fields uses
a stopping rule that necessarily needs a finite upper endpoint
of the marginal distribution of the random field.
In the case of extremal Gaussian random fields,
see \code{\link{MaxStableRF}}, the upper endpoint is
approximated by \code{maxstable.maxGauss}.
Default: \code{3.0} [init].
}
}
The following refers to the simulation of Gaussian random fields
(\code{\link{InitGaussRF}}, \code{\link{GaussRF}}), but most
parts also apply
for the simulation of max-stable random fields
(\code{\link{InitMaxStableRF}}, \code{\link{MaxStableRF}}).
Some of the global parameters determine the basic settings of a
simulation, e.g. \code{direct.method} (which chooses a square
root of a positive definite matrix). The values of
such parameters are read by
\code{\link{InitGaussRF}} and stored in an internal register.
Changing
such a parameter between calling \code{\link{InitGaussRF}} and calling
\code{\link{DoSimulateRF}} or between subsequent calls of
\code{\link{GaussRF}} will not have any effect. These parameters have
the flag "[init]".
Parameters like \code{TBM2.lines} (which determines the number of
i.i.d. processes to be simulated on the line)
are only relevant when generating
random numbers. These parameters are read by \code{DoSimulateRF}
(or by the second part of \code{\link{GaussRF}}), and
are marked by "[do]".
\code{Storing} has an influence on both, \code{\link{InitGaussRF}} and
\code{\link{DoSimulateRF}}. \code{\link{InitGaussRF}} may reserve
more memory if \code{Storing==TRUE}. \code{\link{DoSimulateRF}} will
free the register
if \code{Storing==FALSE}, whatever the value of \code{Storing} was
when \code{\link{InitGaussRF}} was called.
The distinction between [init] and [do] is also relevant if
\code{\link{GaussRF}} is used and called a second time
with the same parameters for the random field and if
\code{RFparameters()$Storing==TRUE}.
Then \code{\link{GaussRF}} realises that the second call has the
same random field parameters, and
takes over the stored intermediate results (that have been calculated
with the \code{RFparameters()} at that time). To prevent the use of
stored intermediate results or to take into account intermediate
changes of RFparameters
set \code{RFparameters(Storing==FALSE)} or use
\code{\link{DeleteRegister}()} between calls of \code{GaussRF}.
A programme that checks whether the parameters are well
adapted to a specific simulation problem is given as an example of
\code{\link{EmpiricalVariogram}()}.
For further details on the implemented methods, see \link{RFMethods}.
}
\value{
If any parameter has been given
\code{RFparameters} returns an invisible list of
the given parameters in full name.
Otherwise the complete list of parameters is returned. Further the
values of the following internal readonly variables are returned
\item{\code{covmaxchar}}{max. name length for variogram/covariance
models}
\item{\code{covnr}}{number of currently implemented
variogram/covariance models}
\item{\code{distrmaxchar}}{max. name length for a distribution}
\item{\code{distrnr}}{number of currently implemented
distributions}
\item{\code{maxdim}}{maximum number of dimensions for a
random field}
\item{\code{maxmodels}}{maximum number of elementary models in
definition of a complex covariance model.}
\item{\code{methodmaxchar}}{max. name length for methods}
\item{\code{methodnr}}{number of currently implemented simulation methods}
}
\references{
Schlather, M. (1999) \emph{An introduction to positive definite
functions and to unconditional simulation of random fields.}
Technical report ST 99-10, Dept. of Maths and Statistics,
Lancaster University.
}
\author{Martin Schlather, \email{schlath@hsu-hh.de}
\url{http://www.unibw-hamburg.de/WWEB/math/schlath/schlather.html}}
\seealso{\code{\link{GaussRF}},
\code{\link{GetPracticalRange}},
\code{\link{MaxStableRF}},
\code{\link{RandomFields}},
and \code{\link{RFMethods}}.}
\examples{
RFparameters(Storing=TRUE)
str(RFparameters())
}
\keyword{spatial}
