mparetomargins

Numeric matrix \(n\times d\). A dataset containing
observations following a multivariate Pareto distribution.

data

Numeric vector with at most \(d\) different elements in
1, ..., \(d\). The variables with respect to which to marginalize
the multivariate distribution.

set_indices

Marginalize a multivariate Pareto dataset <code>data</code> with respect to the
variables in <code>set_indices</code>.

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 (2018) <arXiv:1812.01734>.

Sebastian Engelke

graphicalExtremes

Statistical Methodology for Graphical Extreme Value Models

Adrien S. Hitz

Nicola Gnecco

mparetomargins function

<dl><dt>data</dt>
<dd>Numeric matrix \(n\times d\). A dataset containing
observations following a multivariate Pareto distribution.</dd>
<dt>set_indices</dt>
<dd>Numeric vector with at most \(d\) different elements in
1, ..., \(d\). The variables with respect to which to marginalize
the multivariate distribution.</dd></dl>

Arguments

Marginalize multivariate Pareto dataset — mparetomargins

<dl>

<dt>data</dt>
<dd>Numeric matrix \(n\times d\). A dataset containing
observations following a multivariate Pareto distribution.</dd>


<dt>set_indices</dt>
<dd>Numeric vector with at most \(d\) different elements in
1, ..., \(d\). The variables with respect to which to marginalize
the multivariate distribution.</dd>

</dl>

mparetomargins: Marginalize multivariate Pareto dataset

Description

Usage

Value

Arguments