The uncertainty associated with the use of copulas in multivariate analysis

Changrang Zhou, Ronald van Nooijen*, Alla Kolechkina, Emna Gargouri, Fairouz Slama, Nick van de Giesen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

The dependency structure between hydrological variables is of critical importance to hydrological modelling and forecasting. When a copula capturing that dependence is fitted to a sample, information on the uncertainty of the fit is needed for subsequent hydrological calculations and reasoning. A new method is proposed to report inferential uncertainty in a copula parameter. The method is based on confidence curves constructed with the use of a pseudo maximum likelihood estimator for the copula parameter. The method was tested on synthetic data and then used as a tool in two hydrological examples. The first examines the probability of major floods in two locations on the Rhine River and its tributaries in the same calendar year. In the second example, rainfall–runoff from a karst region in Tunisia was analysed to determine a confidence interval for the delay between precipitation and runoff.

Original languageEnglish
Pages (from-to)2169-2188
Number of pages20
JournalHydrological Sciences Journal
Volume68
Issue number15
DOIs
Publication statusPublished - 2023

Keywords

  • confidence curve
  • copulas
  • coverage probability
  • pseudo maximum likelihood estimator
  • uncertainty analysis

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