Group for Research in Decision Analysis

Inference and model selection for pair-copula constructions

Elif Fidan Acar

Pair-copula constructions (PCCs) provide an elegant way to construct highly flexible multivariate distributions. However, for convenience of inference, pair-copulas are often assumed to depend on the conditioning variables only indirectly. In this talk, I will show how nonparametric smoothing techniques can be used to avoid this assumption. Model selection for PCCs will also be addressed within the proposed method.