Publications

Articles in peer-reviewed journals :

1. Daouia, A., Stupfler, G. and Usseglio-Carleve, A. (2023+). Bias-reduced and variance-corrected asymptotic Gaussian inference about extreme expectiles. Statistics and Computing, to appear. hal

2. Daouia, A., Stupfler, G. and Usseglio-Carleve, A. (2024). An expectile computation cookbook. Statistics and Computing, 34, 103. hal stat&co

3. Daouia, A., Stupfler, G. and Usseglio-Carleve, A. (2023). Inference for extremal regression with dependent heavy-tailed data. Annals of Statistics, 51(5): 2040-2066. hal aos 

4. Stupfler, G. and Usseglio-Carleve, A. (2023). Composite bias-reduced Lp-quantile-based estimators of extreme quantiles and expectiles. Canadian Journal of Statistics, 51(2): 704-742. hal cjs

5. Daouia, A., Stupfler, G. and Usseglio-Carleve, A. (2023). Extreme value modelling of SARS-CoV-2 community transmission using discrete Generalised Pareto distributions. Royal Society Open Science, 10: 220977. hal rsos

6. Arbel, J., Girard, S., Nguyen, H. and Usseglio-Carleve, A. (2023). Multivariate expectile-based distribution: properties, Bayesian inference, and applications. Journal of Statistical Planning and Inference, 225: 146-170. hal jspi Github package

7. Girard, S., Stupfler, G. and Usseglio-Carleve, A. (2022). On automatic bias reduction for extreme expectile estimation. Statistics and Computing, 32, 64. hal stat&co Github package

8. Girard, S., Stupfler, G. and Usseglio-Carleve, A. (2022). Nonparametric extreme conditional expectile estimation. Scandinavian Journal of Statistics, 49:78-115. hal sjs

9. Girard, S., Stupfler, G. and Usseglio-Carleve, A. (2022). Functional estimation of extreme conditional expectiles. Econometrics & Statistics, 21:131-158. hal ecosta

10. Girard, S., Stupfler, G. and Usseglio-Carleve, A. (2021). Extreme conditional expectile estimation in heavy-tailed heteroscedastic regression models. Annals of Statistics, 49(6):3358-3382. hal aos

11. Ag Ahmad, A., Deme, E., Diop, A., Girard, S. and Usseglio-Carleve, A. (2020). Estimation of extreme quantiles of heavy-tailed distributions in a location-dispersion regression model. Electronic Journal of Statistics, 14(2):4421-4456. hal ejs

12. Usseglio-Carleve, A. (2018). Estimation of conditional extreme risk measures from heavy-tailed elliptical random vectors. Electronic Journal of Statistics, 12(2):4057–4093. hal ejs

13. Maume-Deschamps, V., Rullière, D. and Usseglio-Carleve, A. (2018). Spatial expectile predictions for elliptical random fields. Methodology and Computing in Applied Probability, 20(2):643–671. hal mcap 

14. Maume-Deschamps, V., Rullière, D. and Usseglio-Carleve, A. (2017). Quantile predictions for elliptical random fields. Journal of Multivariate Analysis, 159:1–17. hal jmva 

Articles submitted or in revision :

1. Girard, S., Opitz, T. and Usseglio-Carleve, A. (2023). ANOVEX: ANalysis Of Variability for heavy-tailed EXtremes. hal

2. Hambuckers, J., Kratz, M. and Usseglio-Carleve, A. (2023). Efficient estimation in extreme value regression models of hedge fund tail risks. arxiv

3. Ashurbekova, K., Usseglio-Carleve, A., Forbes, F. and Achard, S. (2019). Optimal shrinkage for robust covariance matrix estimators in a small sample size setting. hal

4. Girard, S., Stupfler, G. and Usseglio-Carleve, A. (2019). An Lp−quantile methodology for tail index estimation. hal

Thesis :

• Usseglio-Carleve, A. (2018). Estimation de mesures de risque pour des distributions elliptiques conditionnées. hal