imitlefA: Bivariate Archimedean copula based on integrated...

In YafeiXu/CopulaModel: CopulaModel: Dependence Modeling with Copulas

Description

Bivariate Archimedean copula based on integrated Mittag-Leffler Laplace transform

Usage

pimitlefA(u,v,cpar)
dimitlefA(u,v,cpar)
pcondimitlefA(v,u,cpar)  # C_{2|1}(v|u;cpar)
qcondimitlefA(p,u,cpar,eps=1e-08,mxiter=30,iprint=F) # C_{2|1}^{-1}(p|u;cpar) 
imitlefA.cpar2tau(cpar)
pimitlefAr(u,v,cpar)  # reflected/survival version of pimitlefA
dimitlefAr(u,v,cpar)
pcondimitlefAr(v,u,cpar)  

Arguments

u	value in interval 0,1; could be a vector
v	value in interval 0,1; could be a vector
p	quantile in interval 0,1; could be a vector
cpar	parameter vector: 2-dimensional vector (or 2-column matrix) with parameters vth>0 and de>1.
eps	tolerance for convergence
mxiter	maximum number of iterations
iprint	print flag for iterations

Value

(conditional) cdf or pdf or quantile value(s), or Kendall's tau.

References

Joe H (2014). Dependence Modeling with Copulas. Chapman & Hall/CRC.

Examples

u=seq(.1,.6,.1)
v=seq(.4,.9,.1)
vth=.5; de=1.6; cpar=c(vth,de)
pp=pcondimitlefA(v,u,cpar)
print(pp)
qcondimitlefA(pp,u,cpar)
cdf=pimitlefA(u,v,cpar)
pdf=dimitlefA(u,v,cpar)
tau=imitlefA.cpar2tau(cpar)
print(tau)

YafeiXu/CopulaModel documentation built on May 9, 2019, 11:07 p.m.