Specific {RandomFields}R Documentation

Methods that are specific to certain covariance models

Description

This model determines that the (Gaussian) random field should be modelled by a particular method that is specific to the given covariance model.

Usage

RPspecific(phi, boxcox)

Arguments

phi

object of class RMmodel; specifies the covariance model to be simulated.

boxcox

the one or two parameters of the box cox transformation. If not given, the globally defined parameters are used. see RFboxcox for Details.

Details

RPspecific is used for specific algorithms or specific features for simulating certain covariance functions

Note that RPspecific applies only to the first model or operator in argument phi.

Value

RPspecific returns an object of class RMmodel

Author(s)

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

References

See Also

Gaussian, RP.

Examples

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

## example for implicite use
model <- RMgauss(var=10, s=10) + RMnugget(var=0.1)
plot(model)
plot(RFsimulate(model=model, 0:10, 0:10, n=4))
## The following function shows the internal structure of the model.
## In particular, it can be seen that RPspecific is applied to RMplus.
RFgetModelInfo(level=0, which="internal")

## example for explicite used
model <- RPspecific(RMS(var=unif(min=0, max=10), RMgauss()))
x <- seq(0,10,0.02)
n <- 10

for (i in 1:n) {
  readline(paste("Simulation no.", i, ": press return", sep=""))
  plot(RFsimulate(model, x=x, n=6, seed=i), ylim=c(-5,5))
}



[Package RandomFields version 3.1.50 Index]