thselect.ncpgp

The model tests the null hypothesis of a generalized Pareto above each threshold in <code>thresh</code> against the alternative of a piecewise generalized Pareto model with continuity constraints.

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

thselect.ncpgp function

<dl><dt>xdat</dt>
<dd>[vector] observations</dd>
<dt>thresh</dt>
<dd>[vector] candidate thresholds</dd>
<dt>test</dt>
<dd>[string] indicating whether to perform <code>score</code> test or likelihood ratio (<code>lr</code>) test. The latter requires fitting the alternative model, and so is more computationally expensive.</dd>
<dt>plot</dt>
<dd>[logical]; if <code>TRUE</code>, return a plot with the p-value path.</dd>
<dt>level</dt>
<dd>[double] confidence level for confidence interval, defaults to 0.95</dd>
<dt>...</dt>
<dd>additional arguments, for backward compatibility purposes</dd></dl>

Arguments

Northop and Coleman piecewise generalized Pareto threshold selection diagnostic — thselect.ncpgp

<dl>

<dt>xdat</dt>
<dd>[vector] observations</dd>


<dt>thresh</dt>
<dd>[vector] candidate thresholds</dd>


<dt>test</dt>
<dd>[string] indicating whether to perform <code>score</code> test or likelihood ratio (<code>lr</code>) test. The latter requires fitting the alternative model, and so is more computationally expensive.</dd>


<dt>plot</dt>
<dd>[logical]; if <code>TRUE</code>, return a plot with the p-value path.</dd>


<dt>level</dt>
<dd>[double] confidence level for confidence interval, defaults to 0.95</dd>


<dt>...</dt>
<dd>additional arguments, for backward compatibility purposes</dd>

</dl>

thselect.ncpgp: Northop and Coleman piecewise generalized Pareto threshold selection diagnostic

Description

Usage

Value

Arguments