RandomFields (version 3.1.12)

Strokorb's Functions: Tail correlation function of the Brown-Resnick process

Description

The models define various shape functions for max-stable processes for a given tail correlation function

Usage

RMm2r(phi)
RMm3b(phi)
RMmps(phi)

Arguments

phi

a model for a tail correlation function belonging to the Gneiting class $H_d$

Value

• object of class RMmodel

Details

RMm2r used with RPsmith defines a monotone shape function that corresponds to a tail correlation function belonging to Gneiting's class $H_d$. Currently, the function is implemented for dimensions 1 and 3. Called as such it returns the corresponding monotone function.

RMm3b used with RPsmith defines balls with random radius that corresponds to a tail correlation function belonging to Gneiting's class $H_d$. Currently, the function is implemented for dimensions 1 and 3. (Note that in Strokorb et al. (2014) the density function for twice the radius is considered.) Called as such it returns the corresponding density function for the radius of the balls.

RMmps used with RPsmith defines random hyperplane polygons that corresponds a tail correlaton function belonging to Gneiting's class $H_d$. It currently only allows for RMbrownresnick(RMfbm(alpha=1)) and dimension 2. Called as such it returns the tcf defined by the submodel -- this definition may change in future.

References

• Strokorb, K. (2013)Properties of the Extremal Coefficient Functions.Univ. Goettingen. PhD thesis.
• Strokorb, K., Ballani, F. and Schlather, M. (2014) In Preparation.

See Also

RFsimulate, RMmodel.

Examples

RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
##                   RFoptions(seed=NA) to make them all random again
StartExample()
model <- RMbrownresnick(RMfbm(alpha=1.5, s=0.2))
plot(RMm2r(model))

x <- seq(0, 10, 0.005)
z <- RFsimulate(RPsmith(RMm2r(model), xi=0), x)
plot(z, type="p", pch=20)

FinalizeExample()