I have a PhD in Mathematical Statistics. I did my thesis at MAP5 Laboratory in Université Paris Cité, under the supervision of Fabienne Comte and Céline Duval.
I defended my PhD thesis New Insights on Inverse Problems: Multidimensional Strategies for Deconvolution or Regression, and Ruin Probability Estimation on June 24, 2022. (slides)
Nonparametric Multiple Regression by Projection on Non-compactly Supported Bases. Dussap, F. Annals of the Institute of Statistical Mathematics, 2023.
Nonparametric Estimation of the Expected Discounted Penalty Function in the Compound Poisson Model. Dussap, F. Electronic Journal of Statistics, 16(1):2124–2174, 2022.
Anisotropic multivariate deconvolution using projection on the Laguerre basis. Dussap, F. Journal of Statistical Planning and Inference, 215:23–46, 2021.
Nonparametric Regression by Projection on Non-compactly Supported Bases. 53e Journées de Statistique, June 2022. (slides)
Estimation non paramétrique de la fonction de Gerber–Shiu dans le modèle de Cramér–Lundberg. Groupe de travail de Statistique of the LMRS, May 17, 2022. (slides)
Nonparametric Regression by Projection on Non-compactly Supported Bases. Rencontres Jeunes Statisticien·ne·s, April 2022. (slides)
Estimation non paramétrique de la fonction de Gerber–Shiu dans le modèle de Cramér–Lundberg. Colloque Jeunes Probabilistes et Statisticiens, October 2021. (slides)
Déconvolution sur \(\mathbb{R}_+^d\) par projection sur la base
de Laguerre. 52e Journées
de Statistique, May 2020.
Talk cancelled due to the Covid-19 pandemic.