Bivariate Copula Additive Models for Location, Scale and Shape with Applications in Biomedicine

In many biomedical applications it is worthwhile to model not only the effect that covariates have on the mean but also on other parameters of the response distribution such as variance. Moreover, it is sometimes necessary to study the association between two or more variables and how such associations may depend on certain factors or covariates. Different models of flexible regression have recently been proposed in statistical literature but in this work we will focus on the study of Copula Additive Models for Location, Scale and Shape since this novel approach permits to model the dependence of two variables through copula functions and where covariates are also modelled in a flexible manner. Lastly, the benefits of using these models with real biomedical data will be illustrated.