trans2UFrechet

Empirical and parametric transformation of a dataset to unit Frechet marginal distribution.

models

A set of procedures for parametric and non-parametric modelling of the dependence structure of multivariate extreme-values is provided. The statistical inference is performed with non-parametric estimators, likelihood-based estimators and Bayesian techniques. It adapts the methodologies of Beranger and Padoan (2015) <doi:10.48550/arXiv.1508.05561>, Marcon et al. (2016) <doi:10.1214/16-EJS1162>, Marcon et al. (2017) <doi:10.1002/sta4.145>, Marcon et al. (2017) <doi:10.1016/j.jspi.2016.10.004> and Beranger et al. (2021) <doi:10.1007/s10687-019-00364-0>. This package also allows for the modelling of spatial extremes using flexible max-stable processes. It provides simulation algorithms and fitting procedures relying on the Stephenson-Tawn likelihood as per Beranger at al. (2021) <doi:10.1007/s10687-020-00376-1>.

Simone Padoan

ExtremalDep

Extremal Dependence Models

Boris Beranger

Giulia Marcon

Steven G. Johnson

Rudolf Schuerer 

Brian Gough 

Alec G. Stephenson

Anne Sabourin

Philippe Naveau

trans2UFrechet function

<dl> <dt>data</dt>
<dd>A vector of length \(n\) or a \((n \times p)\) matrix representing the data on its original scale.</dd> <dt>pars</dt>
<dd>A \((1 \times 3)\) vector or a \((p \times 3)\) matrix of marginal GEV parameters. Required when <code>type = "GEV"</code>.</dd> <dt>type</dt>
<dd>A character string indicating the type of transformation. Can be <code>"Empirical"</code> or <code>"GEV"</code>.</dd></dl>

Arguments

Simone Padoan, <a href="/link/simone.padoan%40unibocconi.it?package=ExtremalDep&version=1.0.0" data-mini-rdoc="ExtremalDep::simone.padoan@unibocconi.it">simone.padoan@unibocconi.it</a>,
 <a href="https://faculty.unibocconi.it/simonepadoan/">https://faculty.unibocconi.it/simonepadoan/</a>;
 Boris Beranger, <a href="/link/borisberanger%40gmail.com?package=ExtremalDep&version=1.0.0" data-mini-rdoc="ExtremalDep::borisberanger@gmail.com">borisberanger@gmail.com</a>,
 <a href="https://www.borisberanger.com">https://www.borisberanger.com</a>;

Author

Transformation to Unit Frechet Distribution — trans2UFrechet

<dl>

 <dt>data</dt>
<dd>A vector of length \(n\) or a \((n \times p)\) matrix representing the data on its original scale.</dd>

 <dt>pars</dt>
<dd>A \((1 \times 3)\) vector or a \((p \times 3)\) matrix of marginal GEV parameters. Required when <code>type = "GEV"</code>.</dd>

 <dt>type</dt>
<dd>A character string indicating the type of transformation. Can be <code>"Empirical"</code> or <code>"GEV"</code>.</dd>

</dl>

Simone Padoan, <a href='mailto:simone.padoan@unibocconi.it'>simone.padoan@unibocconi.it</a>,
 <a href='https://faculty.unibocconi.it/simonepadoan/'>https://faculty.unibocconi.it/simonepadoan/</a>;
 Boris Beranger, <a href='mailto:borisberanger@gmail.com'>borisberanger@gmail.com</a>,
 <a href='https://www.borisberanger.com'>https://www.borisberanger.com</a>;

trans2UFrechet: Transformation to Unit Frechet Distribution

Description

Usage

Value

Arguments

Author

Details

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Examples