generate_random_integer_Gamma

Generates a random variogram Matrix by producing a \((d-1) \times (d-1)\) matrix <code>B</code> with random
integer entries between <code>-b</code> and <code>b</code>, computing <code>S = B %*% t(B)</code>,
and passing this <code>S</code> to <code>Sigma2Gamma()</code>.
This process is repeated with an increasing <code>b</code> until a valid Gamma matrix
is produced.

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_integer_Gamma function

<dl><dt>d</dt>
<dd>Number of rows/columns in the output matrix</dd>
<dt>b</dt>
<dd>Initial <code>b</code> used in the algorithm described above</dd>
<dt>b_step</dt>
<dd>By how much <code>b</code> is increased in each iteration</dd></dl>

Arguments

Generate a random Gamma matrix containing only integers — generate_random_integer_Gamma

<dl>

<dt>d</dt>
<dd>Number of rows/columns in the output matrix</dd>


<dt>b</dt>
<dd>Initial <code>b</code> used in the algorithm described above</dd>


<dt>b_step</dt>
<dd>By how much <code>b</code> is increased in each iteration</dd>

</dl>

generate_random_integer_Gamma: Generate a random Gamma matrix containing only integers

Description

Usage

Value

Arguments

See Also

Examples