Title: Semiparametric inference for copulas of mixed data
Authors: Bruno N Remillard - HEC Montreal (Canada) [presenting]
Bouchra R Nasri - McGill University (Canada)
Christian Genest - McGill University (Canada)
Johanna Neslehova - McGill University (Canada)
Abstract: Inference methods are proposed for the estimation of the parameter of a copula family when the unknown marginal distributions are mixtures of discrete and absolutely continuous distribution functions. Under smoothness assumptions, the estimation errors are shown to be Gaussian and their variance can be estimated.