HAC (version 0.1-1)

theta2tau, tau2theta: Kendall's rank correlation coefficient

Description

Kendall's rank correlation coefficient and its inverse.

Usage

theta2tau(theta, type = HAC_GUMBEL)
tau2theta(tau, type = HAC_GUMBEL)

Arguments

theta

the dependency parameter. It can be either a scalar, a vector or a matrix and it is to ensure, that the dependency parameter lies within a certain interval, i.e. $\theta \in [1, \infty)$ for the Gumbel generator and $\theta \in (0, \infty)$ for the Clayto

tau

Kendall's rank correlation coefficient. It can be either a scalar, a vector or a matrix and it is to ensure, that $\tau \in [0,1)$. In the case of the Gaussian copula $\tau \in [-1, 1]$.

type

choose the type between HAC_GUMBEL, AC_GUMBEL, HAC_ROTATED_GUMBEL, HAC_CLAYTON, AC_CLAYTON and GAUSS.

Examples

# computation of the dependency parameter
x = runif(10)
theta = tau2theta(x)

# computation of kendall's tau
y = runif(10, 1, 100)
tau = theta2tau(y)