RandomFields (version 3.0.32)

RMschlather: Covariance Model for binary field based on Gaussian field

Description

RMschlather gives the tail correlation function of the extremal Gaussian process, i.e.

$$C(h) = 1 - \sqrt{ (1-\phi(h)/\phi(0)) / 2 }$$

where $\phi$ is the covariance of a stationary Gaussian field.

Usage

RMschlather(phi, var, scale, Aniso, proj)

Arguments

phi

covariance function of class RMmodel.

var,scale,Aniso,proj

optional arguments; same meaning for any RMmodel. If not passed, the above covariance function remains unmodified.

Value

• RMschlather returns an object of class RMmodel

Details

This model yields the tail correlation function of the field that is returned by RPschlather

See Also

RPschlather RMmodel, RFsimulate,

Examples

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

#Example 1
x <- if (interactive()) 0:1000 else 0:10
model <- RMgauss(scale=50)
z <- RFsimulate(RPschlather(model), x)
plot(z)

y  <- if (interactive()) 0:100 else 0:10
cov <- RFcov(model, y)
ecf <- RFcov(RMschlather(model), y)
matplot(y, cbind(cov, ecf), type="l")


# Example 2
x <- if (interactive()) 0:1000 else 0:10
model <- RMschlather(model)
z <- RFsimulate(RPschlather(model), x)
plot(z)

y  <- if (interactive()) 0:100 else 0:10
cov <- RFcov(model, y)
ecf <- RFcov(RMschlather(model), y)
matplot(y, cbind(cov, ecf), type="l")
FinalizeExample()