margtransf.class

An S4 class to represent the Marginal Transformation

internal

Estimates the p-probability return curve proposed by Murphy-Barltrop et al. (2023) <doi:10.1002/env.2797>. Implements pointwise and smooth estimation of the angular dependence function introduced by Wadsworth and Tawn (2013) <doi:10.3150/12-BEJ471>.

Lídia André

ReturnCurves

Estimation of Return Curves

Callum Murphy-Barltrop

margtransf.class function

<dl>
<dt><code>data</code></dt>
<dd>A matrix containing the data on the original margins.</dd></dl>
<dt><code>qmarg</code></dt>
<dd>A vector containing the marginal quantile used to fit the Generalised Pareto Distribution (GPD) for each variable. Default is <code>rep(0.95, 2)</code>.</dd>
<dt><code>constrainedshape</code></dt>
<dd>Logical. If <code>TRUE</code> (Default), the estimated shape parameter of the Generalised Pareto Distribution (GPD) is constrained to strictly above <code>-1</code>.</dd>
<dt><code>parameters</code></dt>
<dd>A vector containing the scale and shape parameters of the Generalised Pareto Distribution (GPD).</dd>
<dt><code>thresh</code></dt>
<dd>A vector containing the threshold uu above which the Generalised Pareto Distribution (GPD) is fitted.</dd>
<dt><code>dataexp</code></dt>
<dd>A matrix containing the data on standard exponential margins.</dd>

Slots

An S4 class to represent the Marginal Transformation — margtransf.class

<dl>
<dt><code>data</code></dt>
<dd>A matrix containing the data on the original margins.</dd>


<dt><code>qmarg</code></dt>
<dd>A vector containing the marginal quantile used to fit the Generalised Pareto Distribution (GPD) for each variable. Default is <code>rep(0.95, 2)</code>.</dd>


<dt><code>constrainedshape</code></dt>
<dd>Logical. If <code>TRUE</code> (Default), the estimated shape parameter of the Generalised Pareto Distribution (GPD) is constrained to strictly above <code>-1</code>.</dd>


<dt><code>parameters</code></dt>
<dd>A vector containing the scale and shape parameters of the Generalised Pareto Distribution (GPD).</dd>


<dt><code>thresh</code></dt>
<dd>A vector containing the threshold uu above which the Generalised Pareto Distribution (GPD) is fitted.</dd>


<dt><code>dataexp</code></dt>
<dd>A matrix containing the data on standard exponential margins.</dd>


</dl>

margtransf.class: An S4 class to represent the Marginal Transformation

Description

Usage

Arguments

Slots