gpdr.ll

gpdr.ll.optim

Negative log likelihood of the generalized Pareto distribution (return levels)
Negative log likelihood parametrized in terms of log return level and shape in order to perform unconstrained optimization

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

gpdr.ll function

<dl><dt>par</dt>
<dd>vector of length 2 containing \(y_m\) and \(\xi\), respectively the \(m\)-year return level and the shape parameter.</dd>
<dt>dat</dt>
<dd>sample vector</dd>
<dt>m</dt>
<dd>number of observations of interest for return levels. See Details</dd></dl>

Arguments

Negative log likelihood of the generalized Pareto distribution (return levels) — gpdr.ll

<dl>

<dt>par</dt>
<dd>vector of length 2 containing \(y_m\) and \(\xi\), respectively the \(m\)-year return level and the shape parameter.</dd>


<dt>dat</dt>
<dd>sample vector</dd>


<dt>m</dt>
<dd>number of observations of interest for return levels. See Details</dd>

</dl>

Negative log likelihood of the generalized Pareto distribution (return levels)

gpdr.ll: Negative log likelihood of the generalized Pareto distribution (return levels)

Description

Usage

Arguments

See Also