Nonparametric estimation of pair-copula constructions with the empirical pair-copula |
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| Affiliation: | 1. Key Laboratory of Surficial Geochemistry, Ministry of Education, Department of Hydrosciences, School of Earth Sciences and Engineering, State Key Laboratory of Pollution Control and Resource Reuse, Nanjing University, Nanjing, PR China;2. Department of Biological and Agricultural Engineering, Texas A & M University, College Station, TX77843, USA;3. Zachry Department of Civil Engineering, Texas A & M University, College Station, TX77843, USA;4. School of Geographic and Oceanographic science, Nanjing University, Nanjing, PR China;5. School of Hydrology and Water Resources, State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing, PR China |
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| Abstract: | A pair-copula construction is a decomposition of a multivariate copula into a structured system, called regular vine, of bivariate copulae or pair-copulae. The standard practice is to model these pair-copulae parametrically, inducing a model risk, with errors potentially propagating throughout the vine structure. The empirical pair-copula provides a nonparametric alternative, which is conjectured to still achieve the parametric convergence rate. Its main advantage for the user is that it does not require the choice of parametric models for each of the pair-copulae constituting the construction. It can be used as a basis for inference on dependence measures, for selecting an appropriate vine structure, and for testing for conditional independence. |
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| Keywords: | Pair-copula Regular vine Empirical copula Resampling Spearman rank correlation Model selection Independence Smoothing |
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