R: Simulation of Gaussian Random Fields

RPgauss {RandomFields} | R Documentation

## Simulation of Gaussian Random Fields

### Description

This function is used to specify a Gaussian random field that is to be simulated or estimated. Returns an object of class `RMmodel`.

### Usage

    RPgauss(phi, boxcox, stationary_only)

### Arguments

`phi` | the `RMmodel`.

`boxcox` | the one or two parameters of the box cox transformation. If not given, the globally defined parameters are used. see `RFboxcox` for Details.
`stationary_only` | Logical or NA. Used for the automatic choice of methods. `TRUE`: the simulation of non-stationary random fields is refused. In particular, the intrinsic embedding method is excluded and the simulation of Brownian motion is rejected. `FALSE`: intrinsic embedding is always allowed, actually it's the first one considered in the automatic selection algorithm. `NA`: the simulation of the Brownian motion allowed, but intrinsic embedding is not used for translation invariant (“stationary”) covariance models. Default: `NA`

### Value

The function returns an object of class `RMmodel`.

### Note

In most cases, `RPgauss` need not be given explicitely as Gaussian random fields are assumed as default.

`RPgauss` may not find the fastest method neither the most precise one. It just finds any method among the available methods. (However it guesses what is a good choice.) See `RFgetMethodNames` for further information. Note that some of the methods do not work for all covariance or variogram models, see `RFgetModelNames(intern=FALSE)`

By default, all Gaussian random fields have zero mean. Simulating with trend can be done by including `RMtrend` in the model.

`RPgauss` allows to simulate different classes of random fields, controlled by the wrapping model:

If the submodel is a pure covariance or variogram model, i.e. of class `RMmodel`, a corresponding centered Gaussian field is simulated. Not only stationary fields but also non-stationary and anisotropic models can be used, e.g. zonal anisotropy, geometrical anisotropy, separable models, non-separable space-time smodels, multiplicative or nested models; see `RMmodel` for a list of all available models.

### Author(s)

Martin Schlather, schlather@math.uni-mannheim.de http://ms.math.uni-mannheim.de/de/publications/software

### See Also

RP, Gaussian, `RMmodel`, `RFoptions`, `RPbrownresnick`, `RPchi2`, `RPopitz`. `RPt`, `RPschlather`.

Do not mix up with `RMgauss` or `RRgauss`.

### Examples

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

    model <- RMexp()
    x <- seq(0, 10, 0.02)
    plot(model)
    plot(RFsimulate(model, x=x, seed=0))
    plot(RFsimulate(RPgauss(model), x=x, seed=0), col=2) ## the same

[Package RandomFields version 3.1.50 Index]