simulBrownResnick: Simulation of Brown-Resnick random vectors

In r-fndv/mvPot: Multivariate Peaks-over-Threshold Modelling for Spatial Extreme Events

Description

simulBrownResnick provides n replicates of a Brown–Resnick max-stable process with semi-variogram vario at locations loc.

Usage

simulBrownResnick(n, loc, vario, nCores = 1, cl = NULL)

Arguments

n	Number of replicates desired.
loc	Matrix of coordinates as given by expand.grid().
vario	Semi-variogram function.
nCores	Number of cores needed for the computation
cl	Cluster instance as created by makeCluster of the parallel package. Make sure the random number generator has been properly initialized with clusterSetRNGStream().

Details

The algorithm used here is based on the spectral representation of the Brown–Resnick model as described in Dombry et al. (2015). It provides n exact simulations on the unit Frechet scale and requires, in average, for each max-stable vector, the simulation of d Pareto processes, where d is the number of locations.

Value

List of n random vectors drawn from a max-stable Brown–Resnick process with semi-variogram vario at location loc.

References

Dombry, C., Engelke, S. and M. Oesting. Exact simulation of max-stable processes. Biometrika, 103(2), 303-317.

Examples

#Define semi-variogram function
vario <- function(h){
   1 / 2 * norm(h,type = "2")^1.5
}

#Define locations
loc <- expand.grid(1:4, 1:4)

#Simulate data
obs <- simulBrownResnick(10, loc, vario)

r-fndv/mvPot documentation built on Jan. 10, 2020, 2:43 a.m.