| RPprocess {RandomFields} | R Documentation |
Here, all classes of random fields are described that can be simulated.
| Gaussian Random Fields | see Gaussian |
| Max-stable Random Fields | see Maxstable |
| Other Random Fields | Binary field |
| chi2 field | |
| composed Poisson (shot noise, random coin) | |
| t field | |
Martin Schlather, schlather@math.uni-mannheim.de, https://www.wim.uni-mannheim.de/schlather/
RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
## RFoptions(seed=NA) to make them all random again
x <- seq(0, 10, 0.1)
model <- RMexp()
## a Gaussian field with exponential covariance function
z <- RFsimulate(model, x)
plot(z)
## a binary field obtained as a thresholded Gaussian field
b <- RFsimulate(RPbernoulli(model), x)
plot(b)
sum( abs((z@data$variabl1 >=0 ) - b@data$variable1)) == 0 ## TRUE,
## i.e. RPbernoulli is indeed a thresholded Gaussian process