angextrapo

The scale parameter $g(w)$ in the Ledford and Tawn approach is estimated empirically for
$x$ large as $$\frac{\Pr(X_P&gt;xw, Y_P&gt;x(1-w))}{\Pr(X_P&gt;x, Y_P&gt;x)}$$
where the sample ($X_P, Y_P$) are observations on a common unit Pareto scale.
 The coefficient $\eta$ is estimated using maximum likelihood as the
 shape parameter of a generalized Pareto distribution on $\min(X_P, Y_P)$.

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

angextrapo function

<dl><dt>dat</dt>
<dd>an $n$ by $2$ matrix of multivariate observations</dd>
<dt>qu</dt>
<dd>quantile level on uniform scale at which to threshold data. Default to 0.95</dd>
<dt>w</dt>
<dd>vector of unique angles between 0 and 1 at which to evaluate scale empirically.</dd></dl>

Arguments

Bivariate angular dependence function for extrapolation based on rays — angextrapo

<dl>

<dt>dat</dt>
<dd>an $n$ by $2$ matrix of multivariate observations</dd>


<dt>qu</dt>
<dd>quantile level on uniform scale at which to threshold data. Default to 0.95</dd>


<dt>w</dt>
<dd>vector of unique angles between 0 and 1 at which to evaluate scale empirically.</dd>

</dl>

angextrapo: Bivariate angular dependence function for extrapolation based on rays

Description

Usage

Value

Arguments

References

Examples