A modern look at mathematical statistics
Our research activities includes parametric and nonparametric density and regression function estimation. We propose robust alternatives to classical estimators to address the challenges of estimating densities under shape constraints or regression functions in Poisson or logistic regression settings. Our approach is mainly non-asymptotic and considers both the frequentist and Bayesian paradigms.
The SanDAL project – EU funded
Our research is supported by the “ERA Chair in Mathematical Statistics and Data Science – SanDAL” which is a prestigious grant awarded to the University of Luxembourg by the ERA Chairs under the EU’s Horizon 2020 framework programme. With a budget of 2.5 million euros for the period 2019-2024, the project boosts research and training in mathematical statistics and data science. The ERA Chair research activities focuses on two areas: “High-Dimensional Data Analysis” and “New Mathematical Tools for Contemporary Statistics” to develop new and more sophisticated statistical methods