fit_graph_to_Theta

Fits a graph to an empirical Gamma matrix by computing the corresponding
Theta matrix using <code>Gamma2Theta()</code> and greedily chooses <code>m</code> edges that
correspond to high absolute values in Theta.

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

fit_graph_to_Theta function

<dl><dt>data</dt>
<dd>The (standardized) data from which to compute Gamma</dd>
<dt>m</dt>
<dd>The number of edges to add, defaults to the number of edges in a tree</dd>
<dt>Gamma_emp</dt>
<dd>The empirical Gamma matrix
(can be <code>NULL</code> if <code>data</code> is given)</dd></dl>

Arguments

Experimental: Fit graph using empirical Theta matrix — fit_graph_to_Theta

<dl>

<dt>data</dt>
<dd>The (standardized) data from which to compute Gamma</dd>


<dt>m</dt>
<dd>The number of edges to add, defaults to the number of edges in a tree</dd>


<dt>Gamma_emp</dt>
<dd>The empirical Gamma matrix
(can be <code>NULL</code> if <code>data</code> is given)</dd>

</dl>

fit_graph_to_Theta: Experimental: Fit graph using empirical Theta matrix

Description

Usage

Value

Arguments

See Also