RISE

Rethinking and Innovating Statistics for Extremes

Scientific Responsible for the Department: Antonio Canale

Funder: MUR - PRIN 2022

Objectives: RISE aims to rethink the current approaches for extreme value analysis, inspired by the distance between the mathematical assumptions underlying classical extreme value theory and the behavior of real-world processes. These extensions will rely on combining modern statistical alternatives to classical extreme value theory. In particular we will employ Bayesian and frequentist nonparametric and semiparametric methods, extending their use in the field of extreme value statistics.

Partners: