rSchlatherExcess: Simulation of vectors in the maximum domain of attraction of...

In HiDimMaxStable: Inference on High Dimensional Max-Stable Distributions

Description

Generates realisations of vectors in the maximum domain of attraction of a spatial Schlather max-stable distribution.

Usage

rSchlatherExcess(n=500,spatial,params)

Arguments

n	an integer giving the number of observations
spatial	the correlation model given as a list: spatial$sites is a matrix that gives the coordinates of each location. Each row corresponds to one location. spatial$family is an object from the spatial class that gives the spatial model. This must be one of the following family: spatialWhittleMatern for the Whittle Matern correlation model, spatialCauchy for the Cauchy correlation model, spatialPowerExp for the Power exponential model, spatialBessel for the Bessel correlation model
params	A vector of length 2 that must be informed if spatial is given; the first component is for the range parameter and the second component is for the smoothness parameter.

Details

a vector is generated as the product of two independent random variables: a unit Pareto random variable and a Gaussian random vector whose covariance matrix is derived from the spatial model. The package MASS must be loaded to generate Gaussian random vectors

Examples

library(MASS)
rSchlatherExcess(n=500,
  spatial=list(sites=matrix(2*runif(20),ncol=2),family=spatialWhittleMatern),
  params=c(1,2))

HiDimMaxStable documentation built on May 29, 2017, 6:20 p.m.