logdV_HR

Numeric matrix \(n\times d\) or vector with \(d\)
elements.

Numeric vector with
\(\frac{d(d - 1)}{2}\) elements.
It represents the upper triangular portion of a
variogram matrix \(\Gamma\).

Computes the exponent measure density of HR distribution.

Statistical methodology for sparse multivariate extreme value models. Methods are
provided for exact simulation and statistical inference for multivariate Pareto distributions
on graphical structures as described in the paper 'Graphical Models for Extremes' by
Engelke and Hitz (2018) <arXiv:1812.01734>.

Sebastian Engelke

graphicalExtremes

Statistical Methodology for Graphical Extreme Value Models

Adrien S. Hitz

Nicola Gnecco

logdV_HR function

<dl><dt>x</dt>
<dd>Numeric matrix \(n\times d\) or vector with \(d\)
elements.</dd>
<dt>par</dt>
<dd>Numeric vector with
\(\frac{d(d - 1)}{2}\) elements.
It represents the upper triangular portion of a
variogram matrix \(\Gamma\).</dd></dl>

Arguments

Compute the exponent measure density of HR distribution — logdV_HR

<dl>

<dt>x</dt>
<dd>Numeric matrix \(n\times d\) or vector with \(d\)
elements.</dd>


<dt>par</dt>
<dd>Numeric vector with
\(\frac{d(d - 1)}{2}\) elements.
It represents the upper triangular portion of a
variogram matrix \(\Gamma\).</dd>

</dl>

logdV_HR: Compute the exponent measure density of HR distribution

Description

Usage

Value

Arguments