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graphicalExtremes

The goal of graphicalExtremes is to provide an implementation of the statistical methodology paper Engelke and Hitz (2019, JRSSB) for sparse multivariate extreme value models. This includes exact simulation algorithms and statistical inference methods for multivariate Pareto distributions on graphical structures.

Installation

You can install the development version of graphicalExtremes from GitHub with:

# install.packages("devtools")
devtools::install_github("sebastian-engelke/graphicalExtremes")

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Version

Install

install.packages('graphicalExtremes')

Monthly Downloads

605

Version

0.1.0

License

GPL-3

Maintainer

Sebastian Engelke

Last Published

November 8th, 2019

Functions in graphicalExtremes (0.1.0)

emp_chi

Empirical estimation of extremal correlation \(\chi\)
rmpareto

Sampling of a multivariate Pareto distribution
rmpareto_tree

Sampling of a multivariate Pareto distribution on a tree
emp_chi_mat

Empirical estimation of extremal correlation matrix \(\chi\)
dim_Gamma

Is Gamma square matrix?
Gamma2chi

Transformation of the Huesler--Reiss variogram \(\Gamma\) to extremal correlation \(\chi\)
simu_px_dirichlet

Simulate Dirichlet extremal functions
simu_px_HR

Simulate HR extremal functions
data2mpareto

Data standardization to multivariate Pareto scale
Gamma2Sigma

Transformation of \(\Gamma\) matrix to \(\Sigma^{(k)}\) matrix
mst_HR

Fitting of Huesler--Reiss minimum spanning tree
Gamma2chi_3D

Compute theoretical \(\chi\) in 3D
simu_px_tree_HR

Simulate HR extremal functions on a tree
complete_Gamma

Completion of Gamma matrix on block graphs
chi2Gamma

Transformation of extremal correlation \(\chi\) to the Huesler--Reiss variogram \(\Gamma\)
fmpareto_HR

Parameter fitting for multivariate Huesler--Reiss Pareto distribution
Gamma2graph

Transformation of \(\Gamma\) matrix to graph object
select_edges

Select edges to add to a graph
emp_vario

Estimation of the variogram matrix \(\Gamma\) of the Huesler--Reiss distribution
simu_px_tree_dirichlet

Simulate Dirichlet extremal functions on a tree
logLH_HR

Full censored log-likelihood of HR model
Sigma2Gamma

Transformation of \(\Sigma^{(k)}\) matrix to \(\Gamma\) matrix
mparetomargins

Marginalize multivariate Pareto dataset
set_graph_parameters

Set graphical parameters
par2Gamma

Create \(\Gamma\) from vector
fmpareto_graph_HR

Parameter fitting for multivariate Huesler--Reiss Pareto distributions on block graphs
graphicalExtremes

graphicalExtremes: Statistical methodology for graphical extreme value models.
logdV_HR

Compute the exponent measure density of HR distribution
logdVK_HR

Compute censored exponent measure
rmstable

Sampling of a multivariate max-stable distribution
simu_px_tree_logistic

Simulate logistic extremal functions on a tree
rmstable_tree

Sampling of a multivariate max-stable distribution on a tree
simu_px_logistic

Simulate logistic extremal functions
simu_px_neglogistic

Simulate negative logistic extremal functions
unif

Uniform margin
censor

Censor dataset
V_HR

Compute exponent measure
Gamma2par

Extract upper triangular part of \(\Gamma\)