Package: AGCA4extremes 0.1.0

Alberto Quaini

AGCA4extremes: Anchored Geodesic Component Analysis for Extremes

Implements anchored geodesic component analysis for multivariate extremes. The package provides Pareto and rank-Pareto marginal standardization, top-k angular extraction, anchored eigensolutions, reconstruction, diagnostics, nonparametric bootstrap tools, and plotting methods for benchmark-relative angular variation.

Authors:Alberto Quaini [aut, cre]

AGCA4extremes_0.1.0.tar.gz
AGCA4extremes_0.1.0.tar.gz(r-4.7-arm64)AGCA4extremes_0.1.0.tar.gz(r-4.7-x86_64)AGCA4extremes_0.1.0.tar.gz(r-4.6-arm64)AGCA4extremes_0.1.0.tar.gz(r-4.6-x86_64)
AGCA4extremes_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
AGCA4extremes/json (API)

# Install 'AGCA4extremes' in R:
install.packages('AGCA4extremes', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/a91quaini/agca4extremes/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

openblascpp

1.70 score 2 scripts 23 exports 2 dependencies

Last updated from:646e6c8349. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK141
linux-devel-x86_64OK134
source / vignettesOK204
linux-release-arm64OK147
linux-release-x86_64OK127
wasm-releaseOK109

Exports:agcaagca_fit_directionsagca_rank_summaryagca_reconstructagca_residual_riskagca_standardizeagca_variation_explainedanchor_sensitivityanchored_departuresangular_functional_errorbootstrap_agcacanonical_anchordecluster_runsfrechet_anchornormalize_rowspareto_from_cdfprincipal_anchorrank_paretorow_normssimulate_agca_10dsphere_distancetail_directionsthreshold_stability

Dependencies:RcppRcppArmadillo