Nonparametric estimation of simplified vine copula models: comparison of methods

@article{Nagler2017NonparametricEO,
  title={Nonparametric estimation of simplified vine copula models: comparison of methods},
  author={Thomas Nagler and Christian Schellhase and Claudia Czado},
  journal={Dependence Modeling},
  year={2017},
  volume={5},
  pages={120 - 99}
}
Abstract In the last decade, simplified vine copula models have been an active area of research. They build a high dimensional probability density from the product of marginals densities and bivariate copula densities. Besides parametric models, several approaches to nonparametric estimation of vine copulas have been proposed. In this article, we extend these approaches and compare them in an extensive simulation study and a real data application. We identify several factors driving the… 

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