generate_random_graphical_Gamma

Generates a valid Gamma matrix with conditional independence structure
specified by a graph

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 (2020) <doi:10.1111/rssb.12355>.

Sebastian Engelke

graphicalExtremes

Statistical Methodology for Graphical Extreme Value Models

Adrien S. Hitz

Nicola Gnecco

Manuel Hentschel

generate_random_graphical_Gamma function

<dl><dt>graph</dt>
<dd>An <code><a href="/link/igraph%3A%3Agraph?package=graphicalExtremes&version=0.3.2" data-mini-rdoc="graphicalExtremes::igraph::graph">igraph::graph</a></code> object</dd>
<dt>...</dt>
<dd>Further arguments passed to <code>generate_random_spd_matrix()</code></dd></dl>

Arguments

Generate a random Gamma matrix for a given graph — generate_random_graphical_Gamma

<dl>

<dt>graph</dt>
<dd>An <code><a href='https://rdrr.io/pkg/igraph/man/make_graph.html'>igraph::graph</a></code> object</dd>


<dt>...</dt>
<dd>Further arguments passed to <code>generate_random_spd_matrix()</code></dd>

</dl>

generate_random_graphical_Gamma: Generate a random Gamma matrix for a given graph

Description

Usage

Arguments

See Also