Gilles STUPFLER

Professor of Statistics

Université d'Angers

France

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Gilles Stupfler is a Professor of Statistics at the University of Angers, France. His research interests include extreme value theory, statistical inference in heavy-tailed distributions, and the application of statistical methods to modeling complex systems. Recent contributions include works on extreme expectiles, citizen science data analysis, and financial crisis propagation using epidemic modeling. He is actively engaged in advancing methodologies within risk assessment and extreme quantile estimation.

Gilles STUPFLER

Research Interests

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Articles (17)

Abdelaati Daouia and Gilles Stupfler’s contribution to the Discussion of the ‘Discussion Meeting on the Analysis of citizen science data’

Corrected inference about the extreme Expected Shortfall in the general Max-Domain of Attraction

Simple sufficient criteria for second-order extended regular variation in the Gumbel domain of attraction: The case of Weibull-tailed distributions

Describing financial crisis propagation through epidemic modelling on multiplex networks

Bias-reduced and variance-corrected asymptotic Gaussian inference about extreme expectiles

An expectile computation cookbook

Extreme expectile estimation for short-tailed data

Tail Risk Inference via Expectiles in Heavy-Tailed Time Series

Composite bias‐reduced Lp‐quantile‐based estimators of extreme quantiles and expectiles

Extreme value modelling of SARS-CoV-2 community transmission using discrete generalized Pareto distributions

On automatic bias reduction for extreme expectile estimation

Extremile Regression

GARCH-UGH: a bias-reduced approach for dynamic extreme Value-at-Risk estimation in financial time series

Nonparametric extreme conditional expectile estimation

Efficient empirical determination of maximum permissible error in coordinate metrology

The Min-characteristic Function: Characterizing Distributions by Their Min-linear Projections

Beyond tail median and conditional tail expectation: Extreme risk estimation using tail Lp‐optimization

Collaborators (7)

Antoine Usseglio-Carleve

Reuben O'Dea

Laurent Gardes

Yoshinori Kawasaki

Irène Gijbels

Richard Leach

Simone A. PADOAN

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