R: Likelihood for vectors of exceedance with censored components
excess.l
R Documentation
Likelihood for vectors of exceedance with censored components
Description
Computes the likelihood for observations of vectors of exceedances
that belong to the maximum domain of attraction of a multivariate max-stable distribution
whose spectral random vector is Gaussian, Log-normal or has a
clustered copula distribution.
Usage
excess.l(data,ln=FALSE,...)
Arguments
data
a matrix representing the data. Each column corresponds to one observation of a vector of
exceedance with censored components. Note that all components must be larger or equal to one.
ln
logical. If TRUE log-density is computed.
...
further arguments to be passed to mubz.* function
(where * stands for the category
of the model). In particular, category is a character string
indicating
the model to be used:
"normal", "lnormal" or "copula", and
params
gives the values of the
parameters for which the likelihood is computed.
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/excess.l.Rd_%03d_medium.png", width=480, height=480)
> ### Name: excess.l
> ### Title: Likelihood for vectors of exceedance with censored components
> ### Aliases: excess.l
>
> ### ** Examples
>
> raw.data<-rCMS(copulas=c(copClayton,copGumbel),
+ margins=c(marginLnorm,marginFrechet),
+ classes=c(rep(1,4),rep(2,4)),
+ params=c(0.5,1,1.5,1.7),n=50)
> data<-excess.censor(raw.data)
>
> ## No test:
> d<-excess.l(data,params=c(0.5,1,1.5,1.7),
+ category="copula",
+ copulas=c(copClayton,copGumbel),
+ margins=c(marginLnorm,marginFrechet),
+ classes=c(rep(1,4),rep(2,4)))
> ## End(No test)
>
>
>
>
>
> dev.off()
null device
1
>
providing 
.