Multiplication of Random Field Models
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)
RMmodel
s 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)
Martin Schlather, schlather@math.uni-mannheim.de, https://www.wim.uni-mannheim.de/schlather/
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)
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