Simulation of Max-Stable Random Fields
Here, a list of models and methods for simulating max-stable random fields is given.
See also maxstableAdvanced for more advanced examples.
Models
RPbrownresnick |
Brown-Resnick process
using an automatic choice of the 3 RPbr* methods below |
RPopitz |
extremal t process |
RPschlather |
extremal Gaussian process |
RPsmith |
M3 processes |
Methods
RPbrmixed |
simulation of Brown-Resnick processes using M3 representation |
RPbrorig |
simulation of Brown-Resnick processes using the original definition |
RPbrshifted |
simulation of Brown-Resnick processes using a random shift |
Martin Schlather, schlather@math.uni-mannheim.de, https://www.wim.uni-mannheim.de/schlather/
Kabluchko, Z., Schlather, M. & de Haan, L (2009) Stationary max-stable random fields associated to negative definite functions Ann. Probab. 37, 2042-2065.
Schlather, M. (2002) Models for stationary max-stable random fields. Extremes 5, 33-44.
Smith, R.L. (1990) Max-stable processes and spatial extremes Unpublished Manuscript.
RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
## RFoptions(seed=NA) to make them all random again
### currently not programmed
## Not run: \dontshow{
## to do : seq(0, 10, 0.02) oben ist furchtbar langsam. Warum?
}
## End(Not run)
## Not run: \dontshow{
model <- RMball()
x <- seq(0, 10, 5) # nice for x <- seq(0, 10, 0.02)
z <- RFsimulate(RPsmith(model, xi=0), x, n=1000, every=1000)
plot(z)
hist(unlist(z@data), 150, freq=FALSE) #not correct; to do; sqrt(2) wrong
curve(exp(-x) * exp(-exp(-x)), from=-3, to=8, add=TRUE, col=3)
}
## End(Not run)
model <- RMgauss()
x <- seq(0, 10, 0.05)
z <- RFsimulate(RPschlather(model, xi=0), x, n=1000)
plot(z)
hist(unlist(z@data), 50, freq=FALSE)
curve(exp(-x) * exp(-exp(-x)), from=-3, to=8, add=TRUE)
## for some more sophisticated models see maxstableAdvancedPlease choose more modern alternatives, such as Google Chrome or Mozilla Firefox.