margEVT: Regularized Point Processes and Stochastic Marginalization for Extremes

Implements a non-stationary extreme value analysis framework by coupling a covariate-driven non-homogeneous Poisson process (NHPP) with (adaptive) elastic-net regularization and analytical gradients. Provides methods for estimating conditional return levels and unconditional (marginalized) return levels via parametric stochastic integration over stable vector autoregressive VAR(p) covariate trajectories, or non-parametric annual-block resampling. Supports block-specific penalty controls, BIC selection along a regularization path, Karush-Kuhn-Tucker convergence checks, time-rescaling residual diagnostics, conditional parametric bootstrap inference, and walk-forward assessment.

Version:	0.4.0
Imports:	graphics, grDevices, parallel, stats, utils
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0), vars
Published:	2026-10-13
DOI:	10.32614/CRAN.package.margEVT
Author:	Rodrigo Fonseca Villa [aut, cre]
Maintainer:	Rodrigo Fonseca Villa <rodrigo03.villa at gmail.com>
BugReports:	https://github.com/rodrigosqrt3/margEVT/issues
License:	GPL (≥ 3)
URL:	https://github.com/rodrigosqrt3/margEVT
NeedsCompilation:	no
Citation:	margEVT citation info
Materials:	README, NEWS
In views:	ExtremeValue
CRAN checks:	margEVT results

Documentation:

Reference manual:	margEVT.html , margEVT.pdf
Vignettes:	Covariate-driven extremes with margEVT (source, R code)

Downloads:

Package source:	margEVT_0.4.0.tar.gz
Windows binaries:	r-devel: margEVT_0.3.0.zip, r-release: margEVT_0.3.0.zip, r-oldrel: margEVT_0.3.0.zip
macOS binaries:	r-release (arm64): margEVT_0.3.0.tgz, r-oldrel (arm64): margEVT_0.3.0.tgz, r-release (x86_64): margEVT_0.3.0.tgz, r-oldrel (x86_64): margEVT_0.3.0.tgz
Old sources:	margEVT archive

Linking:

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