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Nonparametric estimation of multivariate quantiles

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  • M. Coblenz
  • R. Dyckerhoff
  • O. Grothe

Abstract

In many applications of hydrology, quantiles provide important insights in the statistical problems considered. In this paper, we focus on the estimation of multivariate quantiles based on copulas. We provide a nonparametric estimation procedure for a notion of multivariate quantiles, which has been used in a series of papers. These quantiles are based on particular level sets of copulas and admit the usual probabilistic interpretation that a p‐quantile comprises a probability mass p. We also explore the usefulness of a smoothed bootstrap in the estimation process. Our simulation results show that the nonparametric estimation procedure yields excellent results and that the smoothed bootstrap can be beneficially applied. The main purpose of our paper is to provide an easily applicable method for practitioners and applied researchers in domains such as hydrology and coastal engineering.

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  • M. Coblenz & R. Dyckerhoff & O. Grothe, 2018. "Nonparametric estimation of multivariate quantiles," Environmetrics, John Wiley & Sons, Ltd., vol. 29(2), March.
    • Handle: RePEc:wly:envmet:v:29:y:2018:i:2:n:e2488
    DOI: 10.1002/env.2488
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    Cited by:

    1. Coblenz, Maximilian & Grothe, Oliver & Schreyer, Manuela & Trutschnig, Wolfgang, 2018. "On the length of copula level curves," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 347-365.

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