bb1dep2cpar: BB1 Bivariate copula: mapping of measure of association and...

In YafeiXu/CopulaModel: CopulaModel: Dependence Modeling with Copulas

Description

BB1 Bivariate copula: mapping of one of (beta,tau,rhoS,rhoN) and upper tail dependence lambda to 2-dimensional parameter vector (theta,delta); also mapping of Kendall's tau to copula parameter vector such that lower and upper tail dependence parameters are the same.

Usage

bb1.dep2cpar(value,lmU,type="tau",iprint=F)
bb1.tau2eqlm(tau,destart=1.5,mxiter=30,eps=1.e-6,iprint=F)

Arguments

value	value of dependence measure
lmU	value of upper tail dependence lambda
type	one of "tau", "beta", "rhoS" or "rhoN"
tau	Kendall's tau
iprint	print flag for intermediate results
destart	starting point of delta for iterations, default 1.5
mxiter	maximum number of iterations
eps	tolerance for stopping

Value

2-dimensional copula parameter (theta, delta) if a solution is found for bb1.dep2cpar

vector with th, de, lm1, lmu for bb1.tau2eqlm

See Also

deppar2taurhobetalambda

Examples

bb1.dep2cpar(.4,.1,"beta")
bb1.dep2cpar(.4,.1,"tau")
bb1.dep2cpar(.4,.1,"rhoS")
bb1.dep2cpar(.4,.1,"rhoN")
bb1.tau2eqlm(.4)

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