R: Simulation of vectors in the maximum domain of attraction of...
rCMS
R Documentation
Simulation of vectors in the maximum domain of attraction
of an homogeneous clustered max-stable distribution
Description
Generates realisations of vectors in the maximum domain of attraction
of an homogeneous clustered max-stable distribution.
Usage
rCMS(copulas,margins,classes,params,n=100)
Arguments
copulas
a vector of 'acopula' objects from package copula of length max(classes)
giving the archimedean copulas for each class
margins
a vector of objects of 'margin' class of length max(classes)
giving the marginal distributions for each class
classes
a vector of integers indicating for each component the number of its class
(from 1 to max(classes))
params
a vector of length 2*max(classes),
giving successively the parameters of the archimedean copula and of
the marginal distribution for each class
n
an integer giving the number of observations
Details
a vector is generated as the product of two independent random variables:
a unit Pareto random variable and a random vector whose components are independent
sub-vectors with distributions (copula,margin).
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(HiDimMaxStable)
Loading required package: copula
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/HiDimMaxStable/rCMS.Rd_%03d_medium.png", width=480, height=480)
> ### Name: rCMS
> ### Title: Simulation of vectors in the maximum domain of attraction of an
> ### homogeneous clustered max-stable distribution
> ### Aliases: rCMS
>
> ### ** Examples
>
> raw.data<-rCMS(copulas=c(copClayton,copGumbel),
+ margins=c(marginLnorm,marginFrechet),
+ classes=c(rep(1,10),rep(2,10)),
+ params=c(0.5,1,1.5,1.7),n=1000)
> data<-excess.censor(raw.data)
>
>
>
>
>
> dev.off()
null device
1
>
providing 
.