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copBasic (version 2.2.6)

HRcop: The Hüsler--Reiss Extreme Value Copula

Description

The Hüsler--Reiss copula (Joe, 2014, p. 176) is $$\mathbf{C}_{\Theta}(u,v) = \mathbf{HR}(u,v) = \mathrm{exp}\bigr[-x \Phi(X) - y\Phi(Y)\bigr]\mbox{,}$$ where \(\Theta \ge 0\), \(x = - \log(u)\), \(y = - \log(v)\), \(\Phi(.)\) is the cumulative distribution function of the standard normal distribution, \(X\) and \(Y\) are defined as: $$X = \frac{1}{\Theta} + \frac{\Theta}{2} \log(x/y)\mbox{\ and\ } Y = \frac{1}{\Theta} + \frac{\Theta}{2} \log(y/x)\mbox{.}$$ As \(\Theta \rightarrow 0^{+}\), the copula limits to independence (\(\mathbf{\Pi}\); P). The copula here is a bivariate extreme value copula (\(BEV\)), and the parameter \(\Theta\) requires numerical methods.

Usage

HRcop(u, v, para=NULL, ...)

Value

Value(s) for the copula are returned.

Arguments

u

Nonexceedance probability \(u\) in the \(X\) direction;

v

Nonexceedance probability \(v\) in the \(Y\) direction;

para

A vector (single element) of parameters---the \(\Theta\) parameter of the copula; and

...

Additional arguments to pass.

Author

W.H. Asquith

References

Joe, H., 2014, Dependence modeling with copulas: Boca Raton, CRC Press, 462 p.

See Also

P, GHcop, GLcop, tEVcop

Examples

Run this code
# Parameter Theta = pi recovery through the Blomqvist Beta (Joe, 2014, p. 176)
qnorm(1 - log( 1 + blomCOP(cop=HRcop, para=pi) ) / ( 2 * log(2) ) )^(-1)

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