collaborators

5 papers

math.ST2026

A Kullback-Leibler divergence test for multivariate extremes: theory and practice

Sebastian Engelke, Philippe Naveau, Chen Zhou

Testing whether two multivariate samples exhibit the same extremal behavior is an important problem in various fields including environmental and climate sciences. While several ad…

stat.AP2026

A parsimonious tail compliant multiscale statistical model for aggregated rainfall

Pierre Ailliot, Carlo Gaetan, Philippe Naveau

Modeling rainfall intensity distributions across aggregation scales (from sub-hourly to weekly) is essential for hydrological risk analysis and IDF curves. Aggregation naturally im…

stat.ME2025

Multivariate distributional modeling of low, moderate, and large intensities without threshold selection steps

Carlo Gaetan, Philippe Naveau

In fields such as hydrology and climatology, modelling the entire distribution of positive data is essential, as stakeholders require insights into the full range of values, from l…

stat.ME2025

Joint modeling of low and high extremes using a multivariate extended generalized Pareto distribution

Noura Alotaibi, Matthew Sainsbury-Dale, Philippe Naveau +2

In most risk assessment studies, it is important to accurately capture the entire distribution of the multivariate random vector of interest from low to high values. For example, i…

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…