theta2tau: Kendall's rank correlation coefficient

In HAC: Estimation, Simulation and Visualization of Hierarchical Archimedean Copulae (HAC)

Kendall's rank correlation coefficient

Description

Kendall's rank correlation coefficient and its inverse.

Usage

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

Arguments

theta	the dependency parameter. It can be either a scalar, a vector or a matrix and has to lie within a certain interval, i.e. θ \in [1, ∞) for the Gumbel and Joe family, θ \in (0, ∞) for the Clayton and Frank family and θ \in [0, 1) for the Ali-Mikhail-Haq family.
tau	Kendall's rank correlation coefficient. It can be either a scalar, a vector or a matrix and it is to ensure, that τ \in [0,1).
type	all types are available, see phi for an overview of implemented families.

Examples

# computation of the dependency parameter
x = runif(10)
theta = tau2theta(x, type = 1)

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

HAC documentation built on March 18, 2022, 6:38 p.m.