simu_px_logistic

Simulates logistic extremal functions

internal

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

simu_px_logistic function

<dl><dt>n</dt>
<dd>Number of simulations.</dd>
<dt>d</dt>
<dd>Dimension of the multivariate Pareto distribution.
In some cases this can be <code>NULL</code> and will be inferred from <code>par</code>.</dd>
<dt>idx</dt>
<dd>Integer or numeric vector with <code>n</code> elements. Index/indices from
1 to <code>d</code>, that determine which extremal function to simulate.</dd>
<dt>theta</dt>
<dd>Numeric --- assume \(0 &lt; \theta &lt; 1\).</dd></dl>

Arguments

Simulate logistic extremal functions — simu_px_logistic

<dl>

<dt>n</dt>
<dd>Number of simulations.</dd>


<dt>d</dt>
<dd>Dimension of the multivariate Pareto distribution.
In some cases this can be <code>NULL</code> and will be inferred from <code>par</code>.</dd>


<dt>idx</dt>
<dd>Integer or numeric vector with <code>n</code> elements. Index/indices from
1 to <code>d</code>, that determine which extremal function to simulate.</dd>


<dt>theta</dt>
<dd>Numeric --- assume \(0 &lt; \theta &lt; 1\).</dd>

</dl>

simu_px_logistic: Simulate logistic extremal functions

Description

Usage

Value

Arguments