graphicalExtremes: 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 (2020) <doi:10.1111/rssb.12355>.

Version: 0.2.0
Depends: R (≥ 3.6.0)
Imports: igraph (≥ 1.2.4.1), mvtnorm (≥ 1.0.10), Rdpack, stats (≥ 3.6.0), utils, corpcor, osqp, glmnet, glassoFast, edmcr
Suggests: testthat (≥ 2.1.0), knitr, rmarkdown, dplyr, ggplot2, bookdown, maps
Published: 2022-12-02
Author: Sebastian Engelke [aut, cre], Adrien S. Hitz [aut], Nicola Gnecco [aut], Manuel Hentschel [aut]
Maintainer: Sebastian Engelke <sebastian.engelke at unige.ch>
BugReports: https://github.com/sebastian-engelke/graphicalExtremes/issues
License: GPL-3
URL: https://github.com/sebastian-engelke/graphicalExtremes
NeedsCompilation: no
In views: ExtremeValue
CRAN checks: graphicalExtremes results

Documentation:

Reference manual: graphicalExtremes.pdf
Vignettes: Exercises
Introduction to Extremal Graphical Models

Downloads:

Package source: graphicalExtremes_0.2.0.tar.gz
Windows binaries: r-devel: graphicalExtremes_0.2.0.zip, r-release: graphicalExtremes_0.2.0.zip, r-oldrel: graphicalExtremes_0.1.0.zip
macOS binaries: r-release (arm64): graphicalExtremes_0.2.0.tgz, r-oldrel (arm64): graphicalExtremes_0.2.0.tgz, r-release (x86_64): graphicalExtremes_0.2.0.tgz, r-oldrel (x86_64): graphicalExtremes_0.2.0.tgz
Old sources: graphicalExtremes archive

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