rrlarg

Simulate the <code>r</code>-largest observations from a Poisson point process with intensity
$$\Lambda(x) = (1+\xi(x-\mu)/\sigma)^{-1/\xi}$$.

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

rrlarg function

<dl><dt>n</dt>
<dd>sample size</dd>
<dt>r</dt>
<dd>number of observations per block</dd>
<dt>loc</dt>
<dd>location parameter</dd>
<dt>scale</dt>
<dd>scale parameter</dd>
<dt>shape</dt>
<dd>shape parameter</dd></dl>

Arguments

Simulate r-largest observations from point process of extremes — rrlarg

<dl>

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


<dt>r</dt>
<dd>number of observations per block</dd>


<dt>loc</dt>
<dd>location parameter</dd>


<dt>scale</dt>
<dd>scale parameter</dd>


<dt>shape</dt>
<dd>shape parameter</dd>

</dl>

rrlarg: Simulate r-largest observations from point process of extremes

Description

Usage

Value

Arguments