R: Method to simulate the Nugget effect

Independent Variables {RandomFields}

R Documentation

Method to simulate the Nugget effect

Description

Method to simulate the Nugget effect.

Usage

RPnugget(phi, boxcox, tol, vdim)

Arguments

`phi`	object of class `RMmodel`; specifies the covariance model to be simulated. The only possible model for `phi` is `RMnugget`.
`boxcox`	the one or two parameters of the box cox transformation. If not given, the globally defined parameters are used. see `RFboxcox` for Details.
`tol`	points at a distance less than or equal to `nugget.tol` are considered as being identical. This strategy applies to the simulation method and the covariance function itself. Hence, the covariance function is only positive definite if `nugget.tol=0.0`. However, if the anisotropy matrix does not have full rank and `nugget.tol=0.0` then, the simulations are likely to be odd. The value of `nugget.tol` should be of order 1e-15. Default: `0.0`
`vdim`	positive integer; the model is treated `vdim`-variate, `vdim=1` (default) corresponds to a univariate random field. Mostly, the value of `vdim` is set automatically. Default is that it takes the value of the submodel `phi`

Details

This method only allows RMnugget as a submodel.

The method also allows for zonal nugget effects. Only there the argument tol becomes important. For the zonal nugget effect, the anisotropy matrix Aniso should be given in RMnugget. There, only the kernal of the matrix is important.

Value

RPnugget returns an object of class RMmodel

Author(s)

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

References

Schlather, M. (1999) An introduction to positive definite functions and to unconditional simulation of random fields. Technical report ST 99-10, Dept. of Maths and Statistics, Lancaster University.

Examples

RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
##                   RFoptions(seed=NA) to make them all random again
model <- RMnugget()
z <- RFsimulate(model=model, 0:10, 0:10, n=4)
plot(z)

model <- RPnugget(RMnugget(var=0.01, Aniso=matrix(nc=2, rep(1,4))))
z <- RFsimulate(model=model, 0:10, 0:10, n=4)
plot(z)

[Package RandomFields version 3.1.50 Index]