.rmevA1

This algorithm corresponds to Algorithm 1 in Dombry, Engelke and Oesting (2016),
using the formulation of the Dirichlet mixture of Coles and Tawn (1991)
as described and derived in Boldi (2009) for the bilogistic and extremal
Dirichlet model. Models currently implemented include logistic, negative
logistic, extremal Dirichlet and bilogistic MEV.

internal

Various tools for the analysis of univariate, multivariate and functional extremes. Exact simulation from max-stable processes [Dombry, Engelke and Oesting (2016) <doi:10.1093/biomet/asw008>, R-Pareto processes for various parametric models, including Brown-Resnick (Wadsworth and Tawn, 2014, <doi:10.1093/biomet/ast042>) and Extremal Student (Thibaud and Opitz, 2015, <doi:10.1093/biomet/asv045>). Threshold selection methods, including Wadsworth (2016) <doi:10.1080/00401706.2014.998345>, and Northrop and Coleman (2014) <doi:10.1007/s10687-014-0183-z>. Multivariate extreme diagnostics. Estimation and likelihoods for univariate extremes, e.g., Coles (2001) <doi:10.1007/978-1-4471-3675-0>.

Leo Belzile

Modelling of Extreme Values

Jennifer L. Wadsworth

Paul J. Northrop

Scott D. Grimshaw

Jin Zhang

Michael A. Stephens

Art B. Owen

Raphael Huser

.rmevA1 function

<dl><dt>n</dt>
<dd>sample size</dd>
<dt>d</dt>
<dd>dimension of the multivariate distribution</dd>
<dt>par</dt>
<dd>a vector of parameters</dd>
<dt>model</dt>
<dd>integer, currently ranging from 1 to 9, corresponding respectively to
(1) <code>log</code>, (2) <code>neglog</code>, (3) <code>dirmix</code>, (4) <code>bilog</code>,
(5) <code>extstud</code>, (6) <code>br</code>, (7) <code>ct</code> and <code>sdir</code>, (8) <code>smith</code> and (9) <code>hr</code>.</dd>
<dt>Sigma</dt>
<dd>covariance matrix for Brown-Resnick, Smith and extremal student. Conditionally negative definite
matrix of parameters for the Huesler--Reiss model. Default matrix for compatibility</dd>
<dt>loc</dt>
<dd>matrix of location for Smith model.</dd></dl>

Arguments

Multivariate extreme value distribution sampling algorithm via angular measure — .rmevA1

<dl>

<dt>n</dt>
<dd>sample size</dd>


<dt>d</dt>
<dd>dimension of the multivariate distribution</dd>


<dt>par</dt>
<dd>a vector of parameters</dd>


<dt>model</dt>
<dd>integer, currently ranging from 1 to 9, corresponding respectively to
(1) <code>log</code>, (2) <code>neglog</code>, (3) <code>dirmix</code>, (4) <code>bilog</code>,
(5) <code>extstud</code>, (6) <code>br</code>, (7) <code>ct</code> and <code>sdir</code>, (8) <code>smith</code> and (9) <code>hr</code>.</dd>


<dt>Sigma</dt>
<dd>covariance matrix for Brown-Resnick, Smith and extremal student. Conditionally negative definite
matrix of parameters for the Huesler--Reiss model. Default matrix for compatibility</dd>


<dt>loc</dt>
<dd>matrix of location for Smith model.</dd>

</dl>

.rmevA1: Multivariate extreme value distribution sampling algorithm via angular measure

Description

Usage

Value

Arguments