pickands.liouv

Pickands dependence function as in <cite>Belzile (2014), Proposition 40 and Example 4</cite> and
<cite>Belzile (2014), Proposition 41</cite>, assuming that the parameter alpha is integer-valued.
Returns the Pickands dependence function of the copula domain of attraction (CDA)
of the survival copula, the scaled Dirichlet extreme value model, or the CDA of the copula, the Liouville EV model.

Collections of functions allowing random number generations and
estimation of 'Liouville' copulas, as described in Belzile and Neslehova (2017) <doi:10.1016/j.jmva.2017.05.008>.

Leo Belzile

lcopula

Liouville Copulas

Christian  Genest

Alexander J. McNeil

Johanna G. Neslehova

pickands.liouv function

<dl><dt>t</dt>
<dd>pseudo-angle in (0,1)</dd>
<dt>rho</dt>
<dd>index of regular variation parameter</dd>
<dt>alpha</dt>
<dd>vector of Dirichlet allocations. Currently must be of length 2</dd>
<dt>CDA</dt>
<dd>select the extremal attractor of the copula (<code>C</code>) or the survival copula (<code>S</code>)</dd></dl>

Arguments

Pickands dependence function for the copula domain of attraction of Liouville survival copulas — pickands.liouv

<dl>

<dt>t</dt>
<dd>pseudo-angle in (0,1)</dd>


<dt>rho</dt>
<dd>index of regular variation parameter</dd>


<dt>alpha</dt>
<dd>vector of Dirichlet allocations. Currently must be of length 2</dd>


<dt>CDA</dt>
<dd>select the extremal attractor of the copula (<code>C</code>) or the survival copula (<code>S</code>)</dd>

</dl>

pickands.liouv: Pickands dependence function for the copula domain of attraction of Liouville survival copulas

Description

Usage

Value

Arguments

Examples