gev.Fscore

Firth's modified score equation for the generalized extreme value distribution

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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

gev.Fscore function

<dl><dt>par</dt>
<dd>vector of <code>loc</code>, <code>scale</code> and <code>shape</code></dd>
<dt>dat</dt>
<dd>sample vector</dd>
<dt>method</dt>
<dd>string indicating whether to use the expected ('exp') or the observed ('obs' - the default) information matrix.</dd></dl>

Arguments

Firth's modified score equation for the generalized extreme value distribution — gev.Fscore

<dl>

<dt>par</dt>
<dd>vector of <code>loc</code>, <code>scale</code> and <code>shape</code></dd>


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


<dt>method</dt>
<dd>string indicating whether to use the expected ('exp') or the observed ('obs' - the default) information matrix.</dd>

</dl>

gev.Fscore: Firth's modified score equation for the generalized extreme value distribution

Description

Usage

Arguments

References

See Also