generate_random_spd_matrix

Generates a random \(d \times d\) symmetric positive definite matrix.
This is done by generating a random \(d \times d\) matrix <code>B</code>,
then computing <code>B %*% t(B)</code>,
and then normalizing the matrix to approximately single digit entries.

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_spd_matrix function

<dl><dt>d</dt>
<dd>Number of rows/columns</dd>
<dt>bMin</dt>
<dd>Minimum value of entries in <code>B</code></dd>
<dt>bMax</dt>
<dd>Maximum value of entries in <code>B</code></dd>
<dt>...</dt>
<dd>Ignored, only allowed for compatibility</dd></dl>

Arguments

Generate a random symmetric positive definite matrix — generate_random_spd_matrix

<dl>

<dt>d</dt>
<dd>Number of rows/columns</dd>


<dt>bMin</dt>
<dd>Minimum value of entries in <code>B</code></dd>


<dt>bMax</dt>
<dd>Maximum value of entries in <code>B</code></dd>


<dt>...</dt>
<dd>Ignored, only allowed for compatibility</dd>

</dl>

generate_random_spd_matrix: Generate a random symmetric positive definite matrix

Description

Usage

Arguments

See Also