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, analytical gradients and a
lower bound on the shape parameter.
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, and risk over
planning horizons (design life levels) under covariate scenarios.
Supports block-specific penalty controls, BIC selection along a
regularization path, unpenalized refitting of the selected model,
Karush-Kuhn-Tucker convergence checks, declustering, time-rescaling
residual diagnostics, conditional parametric bootstrap inference, and
walk-forward assessment.
| Version: |
0.6.0 |
| Imports: |
graphics, grDevices, parallel, Rcpp, stats, utils |
| LinkingTo: |
Rcpp |
| Suggests: |
extRemes, knitr, rmarkdown, testthat (≥ 3.0.0), vars |
| Published: |
2026-11-14 |
| 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: |
yes |
| Citation: |
margEVT citation info |
| Materials: |
README, NEWS |
| In views: |
ExtremeValue |
| CRAN checks: |
margEVT results |
Documentation:
Downloads:
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