DoSimulateRF performs an already initialized simulation.
InitSimulateRF internal function;
use InitGaussRF and InitMaxStableRF, instead. SimulateRF internal function;
use GaussRF and MaxStableRF, instead.
DoSimulateRF(n=1, register=0)InitSimulateRF(x, y=NULL, z=NULL, grid, model, param,
method=NULL, register=0, gridtriple=FALSE,
distribution=NA)
SimulateRF(x, y=NULL, z=NULL, grid, model, param, method=NULL,
n=1, register=0, gridtriple=FALSE, distribution=NA)
x,
y, and z should be
interpreted as a grid definition, see Details.CovarianceFct, or
type PrintModelList() to get all optionsparam=c(mean, variance, nugget, scale,...);
the parameters must be given
in this order; further parameters are to be added in case of a
parametrised class of models, see NULL or string; Method used for simulating,
see RFMethods, or
type PrintMethodList() to get all optionsgridtriple==FALSE ascending
sequences for the parameters
x, y, and z are
expected; if gridtriple==TRUE triples of form
c(start,end,step)
expec"Gauss", "Poisson", or "MaxStable".InitSimulateRF returns 0 if no error has occured during the
initialisation process, and a positive value
if failed.
SimulateRF and DoSimulateRF return NULL
if an error has occured; otherwise the returned object
depends on the parameters n and grid:
n==1:
* grid==FALSE. A vector of simulated values is
returned (independent of the dimension of the random field)
* grid==TRUE. An array of the dimension of the
random field is returned.
n>1:
* grid==FALSE. A matrix is returned. The columns
contain the repetitions.
* grid==TRUE. An array of dimension
$d+1$, where $d$ is the dimension of
the random field, is returned. The last
dimension contains the repetitions.GaussRF, MaxStableRF, RandomFields