logdVK_HR

Computes the (censored) exponent measure density of HR distribution.

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

logdVK_HR function

<dl><dt>x</dt>
<dd>Numeric vector with <code>d</code> positive elements
where the censored exponent measure is to be evaluated.</dd>
<dt>K</dt>
<dd>Integer vector, subset of 1, ..., <code>d</code>, the index set that is not censored.
Or logical vector of length <code>d</code>, indicating entries that are not censored.</dd>
<dt>Gamma</dt>
<dd>d x d variogram matrix or numeric vector with d(d-1)/2 elements,
containing the upper triangular part of a variogram matrix.</dd></dl>

Arguments

Compute censored exponent measure — logdVK_HR

<dl>

<dt>x</dt>
<dd>Numeric vector with <code>d</code> positive elements
where the censored exponent measure is to be evaluated.</dd>


<dt>K</dt>
<dd>Integer vector, subset of 1, ..., <code>d</code>, the index set that is not censored.
Or logical vector of length <code>d</code>, indicating entries that are not censored.</dd>


<dt>Gamma</dt>
<dd>d x d variogram matrix or numeric vector with d(d-1)/2 elements,
containing the upper triangular part of a variogram matrix.</dd>

</dl>

logdVK_HR: Compute censored exponent measure

Description

Usage

Value

Arguments