copArchimaxMevlog: cop-ell-psi-psiinv- functions for Archimax Mevlog models.

In satdad: Sensitivity Analysis Tools for Dependence and Asymptotic Dependence

cop-ell-psi-psiinv- functions for Archimax Mevlog models.

Description

Copula function, stable tail dependence function, psi function, psi inverse function for Archimax Mevlog models.

Usage

copArchimaxMevlog(x, ds,  dist = "exp", dist.param = 1)
ellArchimaxMevlog(x, ds)
psiArchimaxMevlog(t, dist = "exp", dist.param = 1)
psiinvArchimaxMevlog(t, dist = "exp", dist.param = 1)

Arguments

x	A vector of size d or a (N.x times d) matrix.
ds	An object of class ds.
dist	The underlying distribution. A character string among "exp" (the default value), "gamma" and "ext".
dist.param	The parameter associated with the choice dist. If dist is "exp", then dist.param is a postive real, the parameter of an exponential distribution. The default value is 1. If dist is "gamma", then dist.param is a vector that concatenates the shape and scale parameters (in this order) of a gamma distribution.
t	A non negative scalar or vector.

Details

The tail dependence structure is set by a ds object. See Section Value in gen.ds.

Turning to Archimax structures, we follow Charpentier et al. (2014). Their algorithm (4.1 of p. 124) has been applied in rArchimaxMevlog to generate observations sampled from the copula

C(x_1,...,x_d) = \psi(\ell(\psi^{-1}(x_1),...,\psi^{-1}(x_d)))

when \ell is here the stable tail dependence function of a Mevlog model. In this package, the stdf function \ell is completely characterized by the ds object. See ellMevlog.

Value

When the underlying distribution dist is

• "exp" ; For a positive \lambda given by dist.param, \psi(t)=\frac{\lambda}{t+\lambda} and \psi^{-1}(t)=\lambda \frac{1-t}{t}.

• "gamma" ; For positive scale \sigma and shape a given by dist.param, \psi(t)=\frac{1}{(t+\sigma)^a} and \psi^{-1}(t)=\frac{t^{-1/a}-1}{\sigma}.

• "ext" ; \psi(t)=\exp(-t) and \psi^{-1}(t)=-\ln(t).

copArchimaxMevlog returns the copula function C(x_1,...,x_d) = \psi(\ell(\psi^{-1}(x_1),...,\psi^{-1}(x_d))).

ellArchimaxMevlog returns the stable tail dependence function \ell(x_1,...,x_d).

psiArchimaxMevlog returns the psi function \psi(t).

psiinvArchimaxMevlog returns the psi inverse function \psi^{-1}(t).

Author(s)

Cécile Mercadier ([e-mail])

References

Charpentier, A., Fougères, A.-L., Genest, C. and Nešlehová, J.G. (2014) Multivariate Archimax copulas. Journal of Multivariate Analysis, 126, 118–136.

See Also

rArchimaxMevlog, gen.ds, ellMevlog

Examples

## Fix a 7-dimensional tail dependence structure
ds7 <- gen.ds(d = 7)

## Fix the parameters for the underlying distribution
(lambda <- runif(1, 0.01, 5))
(shape <- runif(1, 0.01, 5))
(scale <- runif(1, 0.01, 5))

## Fix x and t
x <- c(0.8, 0.9, 0.5, 0.8, 0.4, 0.9, 0.9)
t <- 2

## Evaluate the functions under the underlying exponential construction
copArchimaxMevlog(x = x, ds = ds7, dist = "exp", dist.param = lambda)
ellArchimaxMevlog(x = x, ds = ds7)
psiArchimaxMevlog(t = t, dist = "exp", dist.param = lambda)
psiinvArchimaxMevlog(t = t, dist = "exp", dist.param = lambda)

## Evaluate the functions under the underlying gamma construction
copArchimaxMevlog(x = x, ds = ds7, dist = "gamma", dist.param = c(shape, scale))
ellArchimaxMevlog(x = x, ds = ds7)
psiArchimaxMevlog(t = t, dist = "gamma", dist.param = c(shape, scale))
psiinvArchimaxMevlog(t = t, dist = "gamma", dist.param = c(shape, scale))

satdad documentation built on March 31, 2023, 11:34 p.m.