mubz.copula uses integrate to compute the value of
mu(B,z). If details is TRUE,
mubz.copula returns the integrate return value. If
details is FALSE, mubz.copula returns the value
only.
The types of distributions (with scalar parameter p) in the 'margin' class
are the following: marginUnif is for the Uniform distribution with support
[1-p,1+p]; marginLnorm is for the Lognormal distribution whose the
standard deviation of the normal distribution is equal to p; marginWeibull is for
the Weibull distribution with shape parameter equal to p; marginFrechet is for
the Frechet distribution with shape parameter equal to p; marginGamma is for
the Gamma distribution with shape parameter equal to p; marginGPD is for the
GPD distribution with shape parameter equal to p.
The types of Archimedean copulas are those implemented in the package copula: copAMH,
copClayton, copFrank, copGumbel, copJoe.
Parameters of mubz.copula:
b
a vector of TRUE or FALSE, of length d where d=length(z), TRUE
indicating the coordinates of B
z
a vector of positive constants
params
a vector of length 2*max(classes),
giving successively the parameters of the archimedean copula and of
the marginal distribution for each class
cop
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 coordinate of z the number of its class
(from 1 to max(classes))
See Also
mubz.normal, mubz.lnormal
Examples
# In this example, we compute mu(B,z) for the independent copula
# and Frechet margins.
z<-c(2,3)
kappa<-2
mu<-numeric(2)
mu[1]<-mubz.copula(b=c(TRUE,FALSE),z=z,params=c(1,kappa),
cop=c(copGumbel),margins=c(marginFrechet),classes=c(1,1))
mu[2]<-mubz.copula(b=c(FALSE,TRUE),z=z,params=c(1,kappa),
cop=c(copGumbel),margins=c(marginFrechet),classes=c(1,1))
# Compares mu({1},z)+mu({2},z) with the exact value:
t(mu) %*% z
(sum(1/z^kappa))^(1/kappa)
# For independent components with different distributions,
# one can use any "one-dimensional" copula:
mubz.copula(b=c(TRUE,FALSE),z=z,
params=c(1,2,1,3),cop=c(copGumbel,copGumbel),
margins=c(marginFrechet,marginGamma),classes=c(1,2))
Results
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/mubz.copula.Rd_%03d_medium.png", width=480, height=480)
> ### Name: mubz.copula
> ### Title: mu(B,z) for the copula model
> ### Aliases: mubz.copula
>
> ### ** Examples
>
> # In this example, we compute mu(B,z) for the independent copula
> # and Frechet margins.
> z<-c(2,3)
> kappa<-2
> mu<-numeric(2)
> mu[1]<-mubz.copula(b=c(TRUE,FALSE),z=z,params=c(1,kappa),
+ cop=c(copGumbel),margins=c(marginFrechet),classes=c(1,1))
> mu[2]<-mubz.copula(b=c(FALSE,TRUE),z=z,params=c(1,kappa),
+ cop=c(copGumbel),margins=c(marginFrechet),classes=c(1,1))
> # Compares mu({1},z)+mu({2},z) with the exact value:
> t(mu) %*% z
[,1]
[1,] 0.6009252
> (sum(1/z^kappa))^(1/kappa)
[1] 0.6009252
>
> # For independent components with different distributions,
> # one can use any "one-dimensional" copula:
> mubz.copula(b=c(TRUE,FALSE),z=z,
+ params=c(1,2,1,3),cop=c(copGumbel,copGumbel),
+ margins=c(marginFrechet,marginGamma),classes=c(1,2))
[1] 0.1958086
>
>
>
>
>
> dev.off()
null device
1
>