Research interests

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Current research topics

My research is currently focused on the following themes: I recently created and developed the R package admix, which allows to estimate the unknown parameters of admixture models, to perform hypothesis tests and to do clustering of unknown component densities. The full implementation of this is available to everyone on my Github webpage, so do not hesitate to contribute and suggest me improvements! More on this at the following link, with full package documentation available here. As scientific director of the Research project DIALog (Digital Insurance and Long term risks) with Katrien Antonio, I currently focus on statistical learning and corresponding developments to deal with typical insurance data. In the past, my PhD thesis made me develop many research interests, among which classification issues, generalized linear models and survival analysis. I have been particularly interested in Classification and Regression Trees (CART algorithm), and ensemble methods (e.g. Random Forests).
Considering Generalized Linear Models was straightforward to make comparisons, as an extension to classical regression techniques which enables to specify some different link functions in order to model various response variables. I personnally used the logistic link to model surrender/lapse behaviours, and compared this method with other classification algorithms in a discriminant analysis perspective.
Concerning Survival Analysis, I performed some studies using the famous proportional hazards model by Cox (1972), but also used other intensity models like Weibull or the Accelerated (respectively Decelerated) Failure Time model. I compared these models to competing risks models, an adequate framework to study endpoints (contract lifetime) in life insurance. A natural extension concerns how to deal with censored/truncated data in nonparametric regression techniques such as regression trees.
I also had to deal with problems like overdispersion and heterogeneity. This made me investigate another framework: Finite Mixture Models, and their dynamic extension known as Regime Switching Models. The aim was to develop new results in terms of model selection in this framework. On one hand, my recent research thus focuses on GLM Markov switching models, as well as self-excited processes since they allow us to integrate dynamic correlation between agents. On the other hand, those matters also appear in nonparametric settings, which explains the focus of my recent theoretical research.
Additional information about the DIALog research project and related research topics can be found here.

Published papers and main talks

I would like to thank again my co-authors for these works together. ...and the following talks (non exhaustive list):


I am member of the Editorial Board of Risks.

I reviewed a lot of papers in many journals in Statistics, Probability Theory and Actuarial Sciences. Here is a non-exhaustive list of these journals:

Ph.D. students

I am currently supervising the PhD thesis of three students:


It is with great honnor that I received the following distinctions:

Ph.D. thesis in Applied Mathematics

Title: GLM mixtures and selection of the number of components: application to surrender risk in life insurance. Defended on 07/06/2012, jury: H. Albrecher (president), B. Garel and D. Pommeret (referees), V. Maume-Deschamps and S. Loisel (supervisors), and V. Lepez (examinator).

Manuscript (here).

Slides (defense): here.

Actuarial thesis at AXA Global Life (AGL, AXA Insurance Company):


Segmentation and modelling of surrender behaviours in life insurance. File here.