Package: margEVT 0.4.0

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.

Authors:Rodrigo Fonseca Villa [aut, cre]