_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-graphicalextremes 0.3.3
Propagated dependencies: r-rdpack@2.6.1 r-osqp@0.6.3.3 r-mvtnorm@1.3-2 r-igraph@2.1.1 r-glmnet@4.1-8 r-glassofast@1.0.1 r-cvxr@1.0-15 r-corpcor@1.6.10
Channel: guix-cran
Location: guix-cran/packages/g.scm (guix-cran packages g)
Home page: https://github.com/sebastian-engelke/graphicalExtremes
Licenses: GPL 3
Synopsis: Statistical Methodology for Graphical Extreme Value Models
Description:

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>.

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