Fully Nested 3-Copula: Procedure and Application on Hydrological Data

By F. Serinaldi, Salvatore Grimaldi. 2007

123 citations recorded by the source corpus.

Subfields: Finance, Global and Planetary Change, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/d8f32a9d7a74c4439444f0d48bbd2e56f12f8187

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Citations in the corpus

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).”
Probabilistic assessment of flood risks using trivariate copulas (2012, methodology): “Serinaldi and Grimaldi (2007) applied fully nested Archimedean copulas to two different hydrologic data set, viz., trivariate flood frequency analysis and multivariate sea wave frequency analysis.”
Frequency analysis of droughts using the Plackett copula and parameter estimation by genetic algorithm (2010, unknown): “Serinaldi and Grimaldi (2007) described the inference procedure to carry out a trivariate frequency analysis via asymmetric Archimedean copulas.”
A framework of change‐point detection for multivariate hydrological series (2015, methodology): “…et al., 2000; Burn and Hag Elnur, 2002; Xiong and Guo, 2004; Favre et al., 2004; Salvadori and De Michele, 2004; Grimaldi and Serinaldi, 2006; Serinaldi and Grimaldi, 2007; Zhang and Singh, 2007; Villarini et al., 2009, 2010; Schmocker-Fackel and Naef, 2010; L opez and Franc es, 2013; Bender…”
On the return period and design in a multivariate framework (2011, background): “In addition, since C QV is Archimedean ( Nelsen, 2006), then C QVL is a particular case of a “nested” Archimedean copula (Joe, 1997; Grimaldi and Serinaldi, 2006; Serinaldi and Grimaldi, 2007; H ¨ ardle and Okhrin, 2010; Hering et al., 2010).”
Identification of suitable copulas for bivariate frequency analysis of flood peak and flood volume data (2011, background): “Serinaldi & Grimaldi (2007) highlighted the difference of symmetric and asymmetric dependence structures in fitting Archimedean copulas to trivariate flood and trivariate sea wave data.”
A comparative copula‐based bivariate frequency analysis of observed and simulated storm events: A case study on Bartlett‐Lewis modeled rainfall (2011, background): “Also, a trivariate frequency analysis has been proposed [Genest et al., 2007; Serinaldi and Grimaldi, 2007; Zhang and Singh, 2007b; Grimaldi and Serinaldi, 2006a], in which the issue of mixed association, i.e., both positive and negative or different pairwise associations among the variables…”
Bivariate flood frequency analysis. Part 2: a copula‐based approach with mixed marginal distributions (2009, unknown): “Serinaldi and Grimaldi (2007) describe the inference procedure to carry out a trivariate flood frequency analysis via nested Archimedean copulas.”
Copulas and Its Application in Hydrology and Water Resources (2018, background): “where function u(u), called the generator of the copula, is continuous strictly decreasing function from [0, 1] to [0, ∞) such that u(0) = ∞ and u(1) = 0 (Serinaldi and Grimaldi 2007), and its inverse u is “completely monotone” on [0, ∞), that is u has derivatives of all orders which alternate in si”
Fitting bivariate copulas to the dependence structure between storm characteristics: A detailed analysis based on 105 year 10 min rainfall (2010, methodology): “Some contributions to this topic have already been made: the use of fully nested Archimedean copulas [Grimaldi and Serinaldi, 2006b; Serinaldi and Grimaldi, 2007], multivariate metaelliptical copulas [Genest et al., 2007], and conditional mixtures [De Michele et al., 2007; Salvadori and De Michele,…”
Multivariate return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation (2012, background): “However, limited applications have been developed with more than two variables (Vandenberghe et al., 2010; Pinya et al., 2009; Kao and Govindaraju, 2008, 2007; Genest et al., 2007; Serinaldi and Grimaldi, 2007; Zhang and Singh, 2007; Grimaldi and Serinaldi, 2006a,b).”
Multivariate drought characteristics using trivariate Gaussian and Student t copulas (2013, background): “…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 and Favre, 2008; Villarini et al., 2008; AghaKouchak et al., 2010a, 2010b, 2010c; Chowdhary and Singh, 2010; Wang…”
Meta-elliptical copulas for drought frequency analysis of periodic hydrologic data (2010, background): “Shiau and Shen (2001), Cancelliere and Salas (2004), Shiau (2006), and Mishra and Singh (2008) among others reviewed analyses of these characteristics.”