Description Usage Arguments Details See Also Examples
Computes mu(B,z) for the copula model.
1 | mubz.copula(details=FALSE,...)
|
details |
get more details in the return value? |
... |
See details section. |
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
:
a vector of TRUE or FALSE, of length d
where d=length(z)
, TRUE
indicating the coordinates of B
a vector of positive constants
a vector of length 2*max(classes)
,
giving successively the parameters of the archimedean copula and of
the marginal distribution for each class
a vector of 'acopula' objects from package copula
of length max(classes)
giving the archimedean copulas for each class
a vector of objects of 'margin' class of length max(classes)
giving the marginal distributions for each class
a vector of integers indicating for each coordinate of z
the number of its class
(from 1 to max(classes)
)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | # 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))
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.