rparp: Simulation from R-Pareto processes

In mev: Modelling of Extreme Values

Simulation from R-Pareto processes

Description

Simulation from R-Pareto processes

Usage

rparp(
  n,
  shape = 1,
  riskf = c("sum", "site", "max", "min", "l2"),
  siteindex = NULL,
  d,
  param,
  sigma,
  model = c("log", "neglog", "bilog", "negbilog", "hr", "br", "xstud", "smith",
    "schlather", "ct", "sdir", "dirmix"),
  weights,
  vario,
  coord = NULL,
  ...
)

Arguments

n	number of observations
shape	shape tail index of Pareto variable
riskf	string indicating risk functional.
siteindex	integer between 1 and d specifying the index of the site or variable
d	dimension of sample
param	parameter vector for the logistic, bilogistic, negative bilogistic and extremal Dirichlet (Coles and Tawn) model. Parameter matrix for the Dirichlet mixture. Degree of freedoms for extremal student model. See Details.
sigma	covariance matrix for Brown-Resnick and extremal Student-t distributions. Symmetric matrix of squared coefficients \lambda^2 for the Husler-Reiss model, with zero diagonal elements.
model	for multivariate extreme value distributions, users can choose between 1-parameter logistic and negative logistic, asymmetric logistic and negative logistic, bilogistic, Husler-Reiss, extremal Dirichlet model (Coles and Tawn) or the Dirichlet mixture. Spatial models include the Brown-Resnick, Smith, Schlather and extremal Student max-stable processes.
weights	vector of length m for the m mixture components. Must sum to one
vario	semivariogram function whose first argument must be distance. Used only if provided in conjunction with coord and if sigma is missing
coord	d by k matrix of coordinates, used as input in the variogram vario or as parameter for the Smith model. If grid is TRUE, unique entries should be supplied.
...	additional arguments for the vario function

Details

For riskf=max and riskf=min, the procedure uses rejection sampling based on Pareto variates sampled from sum and may be slow if d is large.

Value

an n by d sample from the R-Pareto process, with attributes accept.rate if the procedure uses rejection sampling.

Examples

rparp(n=10, riskf='site', siteindex=2, d=3, param=2.5, model='log')
rparp(n=10, riskf='min', d=3, param=2.5, model='neglog')
rparp(n=10, riskf='max', d=4, param=c(0.2,0.1,0.9,0.5), model='bilog')
rparp(n=10, riskf='sum', d=3, param=c(0.8,1.2,0.6, -0.5), model='sdir')
vario <- function(x, scale=0.5, alpha=0.8){ scale*x^alpha }
grid.coord <- as.matrix(expand.grid(runif(4), runif(4)))
rparp(n=10, riskf='max', vario=vario, coord=grid.coord, model='br')

mev documentation built on April 20, 2023, 5:10 p.m.