B0413
Title: On factor copula-based mixed regression models
Authors: Bouchra Nasri - University of Montreal (Canada)
Bruno N Remillard - HEC Montreal (Canada)
Pavel Krupskiy - Melbourne University (Australia) [presenting]
Abstract: A copula-based method for mixed regression models is introduced, 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 the asymptotic behaviour of the estimation errors is found. 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. All developed methodologies are implemented in CopulaGAMM available in CRAN.
