3 papers
stat.ME2026
Benchmark of Likelihood-Free Inference Methods based on Neural and Optimal Transport Approaches
Samira Aka, Marie Kratz, Philippe Naveau
Simulation-based inference (SBI) has become an increasingly important framework for parameter estimation in models for which simulation is feasible, including cases where likelihoo…
stat.AP2026
Likelihood-Free Inference for Multivariate Generalized Pareto Models
Samira Aka, Marie Kratz, Philippe Naveau
Likelihood-based inference for multivariate extreme-value models is often unreliable or infeasible when likelihoods are intractable or supports are discrete. This challenge is part…
stat.ME2025
Multivariate Discrete Generalized Pareto Distributions: Theory, Simulation, and Applications to Dry spells
Samira Aka, Marie Kratz, Philippe Naveau
This article extends the multivariate extreme value theory (MEVT) to discrete settings, focusing on the generalized Pareto distribution (GPD) as a foundational tool. The purpose of…