Copula modeling has been part of the scientific landscape for over a quarter-century. Statistical techniques and computer software are now available for making inference and prediction based on parametric copula models and, at least for problems involving small to moderate numbers of variables, these tools have proved effective in various fields of application, most notably finance, insurance, and hydrology. Owing to its success, copula modeling is now gradually being applied to entirely new situations involving large collections of discrete and continuous variables and high volumes of data that are either structured, e.g., due to sampling, or subject to phenomena such as censoring, clustering, or contamination.
The objective of this workshop is to take stock of new developments in copula modeling, to bring together some of the most active researchers in the field, and to identify the current challenges in dependence modeling faced in areas such as economics, health sciences, and the environment, where the copula approach to modeling is emerging. The overall goal is to gain a collective view of recent advances in this field, to generate new ideas and training opportunities, as well as to foster interaction between members of the collaborative research team on the CANSSI-funded project "Copula Dependence Modeling: Theory and Applications."