Date: 2026-03-13

Time: 15:30-16:30 (Montreal time)

Location: In person, Burnside 1104

https://mcgill.zoom.us/j/82187303482

Meeting ID: 821 8730 3482

Passcode: None

Abstract:

In this talk, we propose a copula-based framework for regression modelling in which the conditional distribution of the response variable, given covariates, is specified through a parametric family of continuous or discrete distributions. For mixed models, we incorporate cluster-level dependence by introducing a common latent factor modeled via a factor copula. We discuss the estimation of both the copula parameters and the marginal parameters, and we derive the asymptotic behavior of the resulting estimators. Numerical experiments are performed to assess the precision of the estimators for finite samples. An example of an application is given using COVID-19 vaccination hesitancy from several countries. This is a joint work with Pavel Krupskii and Bruno Remillard.

Speaker

Professor Nasri is a faculty member of Biostatistics in the Department of Social and Preventive Medicine. Prof. Nasri holds an FRQS Junior 2 award and is a principal investigator on grants funded by NSERC and CIHR in theoretical statistics for complex data and mathematical modelling for infectious diseases.  Since March 2023, she has been nominated as Chair of PathCheck’s Data Informatics Center of Epidemiology and since 2024, she has been a co-director of the digital health network in Québec. Prof. Nasri authored and co-authored several papers on time series, dependence modelling, multivariate statistics, and mathematical modelling for infectious diseases.