Subjects by keyword
Our faculty members and researchers have vast expertise in many advanced aeras, as can be seen in the list below.
For the complete list of our experts, see the Departmental directory.
- Bayesian statistics
- Markov chain Monte Carlo methods
- Model/variable selection
- Regression methods
- Robust statistics
My research interests are Bayesian robustness against outliers and Markov chain Monte Carlo methods. I more precisely introduced methodology for obtaining robust model/variable selection and parameter estimation in linear regression, along with efficient algorithms for achieving these tasks. My research has so far been more on the theoretical/methodological side. My objective for the next years is to apply in actuarial science the tools I developed, and to introduce sophisticated methods of interest for actuaries. In particular, I want to develop an automatic data analysis procedure in which the models are robust and trained through a full and exact Bayesian analysis. See my personal web page for more details and a list of my publications.
Advertisement: I am looking for students with a strong background in either: theoretical statistics (mainly probability and analysis), applied statistics and actuarial science, and computer science (the plan is also to develop R packages for a user-friendly and efficient implementation of the methods). There exist multiple funding opportunities (see, e.g., https://www.nserc-crsng.gc.ca/ et http://www.frqnt.gouv.qc.ca/en/accueil). It is even possible for non-Canadians to apply for FRQNT scholarships. Please do not hesitate to contact me if you are interested. I aim to provide an environment to my students in actuarial science and statistics that is equitable, inclusive and diversified. In particular, recruiting will be done according to Université de Montréal's Equity, Diversity and Inclusion policy.