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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

Details

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

See Also

RPschlather RMmodel, RFsimulate,

Examples

Run this code
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()

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