A0456
Title: On factor copula-based mixed regression models
Authors: Bouchra Nasri - University of Montreal (Canada) [presenting]
Pavel Krupskiy - Melbourne University (Australia)
Bruno Remillard - HEC Montreal (Canada)
Abstract: A copula-based method for mixed regression models is proposed, where the conditional distribution of the response variable, given covariates, is modelled by a parametric family of continuous or discrete distributions, and the effect of a common latent variable pertaining to a cluster is modelled with a factor copula. It is shown how to estimate the parameters of the copula and the parameters of the margins and find the asymptotic behavior of the estimation errors. 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.
