shape.trimhill

Given a sample of Pareto-tailed samples (positive tail index),
compute the trimmed Hill estimator. If \(k0=k\), the estimator
reduces to Hill's estimator for the shape index

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

Raphael Huser

Scott D. Grimshaw

Jin Zhang

Michael A. Stephens

Art B. Owen

shape.trimhill function

<dl><dt>xdat</dt>
<dd>[numeric] vector of positive observations</dd>
<dt>k</dt>
<dd>[integer] number of order statistics for the threshold</dd>
<dt>k0</dt>
<dd>[integer] number of largest order statistics, strictly less than <code>k</code></dd>
<dt>sorted</dt>
<dd>[logical] if <code>TRUE</code>, data are assumed to be sorted in decreasing order</dd></dl>

Arguments

Trimmed Hill estimator for the shape parameter — shape.trimhill

<dl>

<dt>xdat</dt>
<dd>[numeric] vector of positive observations</dd>


<dt>k</dt>
<dd>[integer] number of order statistics for the threshold</dd>


<dt>k0</dt>
<dd>[integer] number of largest order statistics, strictly less than <code>k</code></dd>


<dt>sorted</dt>
<dd>[logical] if <code>TRUE</code>, data are assumed to be sorted in decreasing order</dd>

</dl>

shape.trimhill: Trimmed Hill estimator for the shape parameter

Description

Usage

Value

Arguments

References