collaborators

5 papers

stat.ME2026

Continuous mixtures of Gaussian processes as models for spatial extremes

Lorenzo Dell'Oro, Carlo Gaetan, Thomas Opitz

Spatial modelling of extreme values allows studying the risk of joint occurrence of extreme events at different locations and is of significant interest in climatic and other envir…

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

Flexible space-time models for extreme data

Lorenzo Dell'Oro, Carlo Gaetan

Extreme value analysis is an essential methodology in the study of rare and extreme events, which hold significant interest in various fields, particularly in the context of enviro…