The course covers basic econometric models and methods that are routinely applied to obtain inference results in economic and financial applications. ...
This course covers recent methodology for causal inference in settings with time-varying exposures (longitudinal data) and causally connected units (interference). We will consider theory for identification and estimation of effects, illustrated by real-li ...
In the decades from 1930 to 1950, many rank-based statistics were introduced. These methods were received with much interest, because they worked under weak conditions. Starting in the late 1950, a theory of robustness was added. The course gives an overvi ...
Présenter aux étudiants:
1 - les notions de base de l'accidentologie industrielle par le biais du traitement de cas concrets (processus chimiques, stockages pétroliers, gazoduc,...)
2 - la mise en oeuvre des méthodologies usuelles d'analyse des dangers et ...
This course is intended to give a brief overview of how to prove consistency results in nonparametric regression. In particular, we will focus on least-square regression estimators. Some connections to the empirical risk minimization (ERM) problem will be ...
The literature on nonlinear signal processing has exploded, and it becomes more and more difficult to identify the most useful approaches for specific contexts. This course presents promising developments for the practical application of nonlinear signal m ...