SimulateRF {RandomFields} | R Documentation |
DoSimulateRF
performs an already initialised simulation.
InitSimulateRF
internal function;
use InitGaussRF
and InitMaxStableRF
, instead.
DoSimulateRF(n=1, register=0, paired=FALSE, trend=NULL) InitSimulateRF(x, y=NULL, z=NULL, T=NULL, grid=!missing(gridtriple), model, param, trend, method=NULL, register=0, gridtriple, distribution=NA)
x |
matrix of coordinates, or vector of x coordinates |
y |
vector of y coordinates |
z |
vector of z coordinates |
T |
time instances |
grid |
logical; determines whether the vectors |
model |
string; covariance or variogram model,
see |
param |
vector or list.
|
method |
|
register |
0:9; place where intermediate calculations are stored; the numbers are aliases for 10 internal registers |
gridtriple |
logical; if |
distribution |
marginal distribution: |
n |
number of realisations to generate; if |
paired |
logical. |
trend |
only used for universal and intrinsic kriging. In case of
universal kriging |
InitSimulateRF
returns 0 if no error has occurred during the
initialisation process, and a positive value if failed.
DoSimulateRF
returns NULL
if an error has occurred; 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 realisations.
* grid=TRUE
. An array of dimension
d+1, where d is the dimension of
the random field, is returned. The last
dimension contains the realisations.
Martin Schlather, martin.schlather@math.uni-goettingen.de http://www.stochastik.math.uni-goettingen.de/~schlather
GaussRF
, MaxStableRF
, RandomFields