2005•Unpublished venueRequires access

Application of copulas to multivariate hydrological frequency analysis

Yuan Han-fang

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Abstract

The definition,the properties and the construction methods of copulas are introduced.An application example of copula as the joint distribution function for the annual maximum floods on the two neighboring hydrological stations,which are located at the same river,is established using the bivariate Clayton-type copula.The results show that the copula-constructed joint distribution function can well fit the observed data.Considering that copulas can be constructed on the basis of a variety of marginal distribution functions,which are very flexible for a wide range of applications,it is recommended to be employed in the multivariate hydrological frequency analysis.

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What this paper is about

The definition,the properties and the construction methods of copulas are introduced.An application example of copula as the joint distribution function for the annual maximum floods on the two neighboring hydrological stations,which are located at the same river,is established using the bivariate Clayton-type copula.The results show that the copula-constructed joint distribution function can well fit the observed data.Considering that copulas can be constructed on the basis of a variety of marginal distribution functions,which are very flexible for a wide range of applications,it is recommended to be employed in the multivariate hydrological frequency analysis.

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Available abstract

The definition,the properties and the construction methods of copulas are introduced.An application example of copula as the joint distribution function for the annual maximum floods on the two neighboring hydrological stations,which are located at the same river,is established using the bivariate Clayton-type copula.The results show that the copula-constructed joint distribution function can well fit the observed data.Considering that copulas can be constructed on the basis of a variety of marginal distribution functions,which are very flexible for a wide range of applications,it is recommended to be employed in the multivariate hydrological frequency analysis.

Key concepts: Copula (linguistics), Bivariate analysis, Multivariate statistics, Joint probability distribution, Marginal distribution, Multivariate normal distribution, Mathematics, Econometrics

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