| RMmult {RandomFields} | R Documentation |
RMmult is a multivariate covariance model which depends on
up to 10 submodels C_0, C_1, ..., C_10.
In general, realizations of the created RMmodel are pointwise
product of independent realizations of the submodels.
In particular, if all submodels are given through a covariance function, the resulting model is defined through its covariance function, which is the product of the submodels' covariances.
RMmult(C0, C1, C2, C3, C4, C5, C6, C7, C8, C9, var, scale, Aniso, proj)
C0 |
an |
C1,C2,C3,C4,C5,C6,C7,C8,C9 |
optional; each an |
var,scale,Aniso,proj |
optional arguments; same meaning for any
|
RMmodels can also be multiplied via the
*-operator, e.g.: C0 * C1
The global arguments scale,Aniso,proj of RMmult
are multiplied to the corresponding argument of the submodels
(from the right side). E.g.,
RMmult(Aniso=A1, RMexp(Aniso=A2), RMspheric(Aniso=A3))
equals
RMexp(Aniso=A2 %*% A1) * RMspheric(Aniso=A3 %*% A1)
In case that all submodels are given through a covariance function,
the global argument var of RMmult
is multiplied to the product covariance of RMmult.
RMmult returns an object of class RMmodel
Martin Schlather, schlather@math.uni-mannheim.de
RMplus,
RMmodel,
RMprod,
RFsimulate,
RFfit.
RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set ## RFoptions(seed=NA) to make them all random again # separable, multiplicative model model <- RMgauss(proj=1) * RMexp(proj=2, scale=5) z <- RFsimulate(model=model, 0:10, 0:10, n=4) plot(z)