RMmult: Multiplication of Random Field Models
In RandomFields: Simulation and Analysis of Random Fields

Description Usage Arguments Details Value See Also Examples

RMmult is a multivariate covariance model which depends on up to 10 submodels C_0, C_1, ..., C_9. In general, realizations of the created RMmodel are pointwise products 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.

1	RMmult(C0, C1, C2, C3, C4, C5, C6, C7, C8, C9, var, scale, Aniso, proj)

`C0`	an `RMmodel`.
`C1,C2,C3,C4,C5,C6,C7,C8,C9`	optional; each an `RMmodel`.
`var,scale,Aniso,proj`	optional arguments; same meaning for any `RMmodel`. If not passed, the above model remains unmodified.

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.

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)