theta2tau function

Kendall's rank correlation coefficient

Kendall's rank correlation coefficient and its inverse.

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. $\theta \in [1, \infty)$ for the Gumbel and Joe family, $\theta \in (0, \infty)$ for the Clayton and Frank family and $\theta \in [0, 1)$ 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 $\tau \in [0,1)$.
• 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)