Metaelliptical copulas and their use in frequency analysis of multivariate hydrological data

By Christian Genest, Anne-Catherine Favre, Julie Béliveau, Christine Jacques. 2007

248 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/e97cbc76a0d7c7aee95782900fcca0170403f80d

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In Global and Planetary Change

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Citations in the corpus

Trivariate statistical analysis of extreme rainfall events via the Plackett family of copulas (2008, methodology): “[28] The quantity yUV in (20) can also be estimated by maximizing the pseudolikelihood function [ Genest et al., 1995 ], similar to the maximum likelihood method used in univariateanalysis.Forn vedsamples(uk,vk),k=1, ... , n, the pseudolikelihood function L can be expressed as”
Bivariate flood frequency analysis. Part 2: a copula‐based approach with mixed marginal distributions (2009, background): “Details of the goodnessof-fit tests for copulas can be found in Panchenko (2005) and Genest et al. (2007b). In the next subsection, the conditional distributions and return periods for different combinations of flood characteristics are evaluated.”
Probabilistic assessment of flood risks using trivariate copulas (2012, methodology): “Genest et al. (2007) applied meta-elliptical copulas for multivariate frequency analysis of annual spring flood at Romaine River in Québec, Canada and concluded that meta-elliptical copulas can help in better modeling the dependence structure of random variables when observed differences between…”
Weighted likelihood copula modeling of extreme rainfall events in Connecticut. (2010, methodology): “Recent 267 research has shown the importance of modeling them jointly (Genest et al., 2007; Kao and 268 Govindaraju, 2008), but existing works are mostly with data at a lower frequency.”
Probabilistic modeling of flood characterizations with parametric and minimum information pair-copula model (2016, methodology): “In particular, these models have been widely used in multivariate analysis of hydrological data (Genest et al., 2007, 2009; Grimaldi and Serinaldi, 2006; Salvadori et al., 2007; Serinaldi and Grimaldi, 2007; Yan et al., 2007; Zhang and Singh, 2007; Song and Singh, 2010).”
Copula Theory: An Introduction (2010, unknown): “For more details, see [61, 62, 67, 77, 137].”
Multivariate drought characteristics using trivariate Gaussian and Student t copulas (2013, methodology): “…2007; De Michele et al., 2005; Grimaldi and Serinaldi, 2006; Shiau et al., 2006; Zhang and Singh, 2006, 2007a, 2007b, 2007c; Genest and Favre, 2007; Genest et al., 2007a, 2007b; Kao and Govindaraju, 2007a, 2007b, 2008; Poulin et al., 2007; Renard and Lang, 2007; Serinaldi and Grimaldi, 2007; Evin…”