RMplus: Addition of Random Field Models

Description

RMplus is an additive covariance model which depends on up to 10 submodels $C_0, C_1, ..., C_10$. In general, realizations of the created RMmodel are pointwise sums 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 sum of the submodels' covariances. Analogously, if all submodels are given through a variogram.

Usage

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

Arguments

an RMmodel.

C1,C2,C3,C4,C5,C6,C7,C8,C9

optional; each an RMmodel.

var,scale,Aniso,proj

optional parameters; same meaning for any RMmodel. If not passed, the above model remains unmodified.

Value

RMplus returns an object of class RMmodel

Details

RMmodels can also be summed up via the +-operator, e.g.: C0 + C1

The global parameters var,scale,Aniso,proj of RMplus are multiplied to the corresponding parameters of the submodels (from the right side).

Examples

Run this code

set.seed(0)
model <- RMgauss() + RMnugget(var=0.01)
z <- RFsimulate(model=model, 0:10, 0:10, grid=TRUE, n=4)
plot(z)


# gives the same model as 
model <- RMplus(RMgauss(), RMnugget(var=0.01))
z <- RFsimulate(model=model, 0:10, 0:10, grid=TRUE, n=4)
plot(z)

Run the code above in your browser using DataLab

Data engineering and BI courses are free!