R: Scaling operator

RMS {RandomFields} | R Documentation

## Scaling operator

### Description

`RMS` is an operator that modifies the variance and the coordinates or distances of a submodel φ by

C(h) = v * φ(A*h/s).

Most users will never call `RMS` directly, see the details.

### Usage

    RMS(phi, var, scale, Aniso, proj, anisoT)

### Arguments

`phi` | submodel
`var` | is the optional variance parameter v, It can be also an arbitrary non-negative function.
`scale` | scaling parameter s which is positive
`Aniso` | matrix or `RMmodel`. The optional anisotropy matrix A, multiplied from the right by a distance vector x, i.e. Ax
`proj` | is the optional projection vector which defines a diagonal matrix of zeros and ones and `proj` gives the positions of the ones (integer values between 1 and teh dimension of x).
`anisoT` | the transpose of the anisotropy matrix B, multiplied from the left by a distance vector x, i.e. x^\top B.

### Details

The call in the usage section is equivalent to `phi(..., var, scale, anisoT, Aniso, proj)`, where `phi` has to be replaced by a valid `RMmodel`

Most users will never call `RMS` directly.

### Value

`RMS` returns an object of class `RMmodel`.

### Note

At most one of the arguments, `Aniso`, `anisoT` and `proj` may be given at the same time.

### Author(s)

Martin Schlather, schlather@math.uni-mannheim.de

### See Also

`RMmodel`,

`RMprod` for an alternative way to define an arbitrary, location dependent variance. There the standard deviation is given so that `RMprod` might be used even in the multivariate case.

### Examples

    RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
    ##                   RFoptions(seed=NA) to make them all random again

    model1 <- RMS(RMexp(), scale=2)
    model2 <- RMexp(scale=2)
    x <- seq(0, 10, 0.02)
    print(all(RFcov(model1, x) == RFcov(model2, x))) # TRUE

[Package RandomFields version 3.1.50 Index]