graphicalExtremes v0.1.0

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Statistical Methodology for Graphical Extreme Value Models

Statistical methodology for sparse multivariate extreme value models. Methods are provided for exact simulation and statistical inference for multivariate Pareto distributions on graphical structures as described in the paper 'Graphical Models for Extremes' by Engelke and Hitz (2018) <arXiv:1812.01734>.

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graphicalExtremes

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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")

Functions in graphicalExtremes

Name Description
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 \(\Gamma\)
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Details

License GPL-3
Encoding UTF-8
LazyData true
RoxygenNote 6.1.1
RdMacros Rdpack
NeedsCompilation no
Packaged 2019-11-06 18:03:38 UTC; engelkes
Repository CRAN
Date/Publication 2019-11-08 09:40:02 UTC

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