Extremes in Nature

By G. Salvadori, Carlo De Michele, N. T. Kottegoda, Renzo Rosso. 2007

233 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/53b816556484218ab0865fd89ed290fc65a00bbf

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Citations in the corpus

Modelling bivariate rainfall distribution and generating bivariate correlated rainfall data in neighbouring meteorological subdivisions using copula (2010, background): “It joins or ‘couples’ multivariate distribution functions to their corresponding marginal distribution functions (Poulin et al., 2007; Salvadori et al., 2007).”
On the construction of multivariate extreme value models via copulas (2009, methodology): “These models have quite a few distinguished properties: (1) a suitable number of parameters can be considered, a feature of great importance in applications; (2) the parameters can be interpreted in terms of new multivariate measures of association and/or dependence (Nelsen, 1996; Schmid and Schmidt”
Random Fields Simplified: Preserving Marginal Distributions, Correlations, and Intermittency, With Applications From Rainfall to Humidity (2020, background): “…which in turn corresponds to a separable STCS in the multiplicative form (on the condition that it is positive definite) ρ δ; τ; θð Þ ¼ FS δ; θSð Þ·FT τ; θTð Þ (19) For the Clayton copula in equation (17), the product copula corresponds to limiting case θ = 0 (Salvadori et al., 2007; p. 237).”
Copula Theory: An Introduction (2010, background): “At the same time, different fields like hydrology [76, 176] discovered the importance of this concept for constructing more flexible multivariate models.”
Bivariate frequency analysis of nonstationary low‐flow series based on the time‐varying copula (2015, methodology): “In describing the dependence structure as well as the joint distribution of multiple hydrological random variables, the copula function (Nelsen, 2006; Salvadori et al., 2007) has been widely applied (De Michele and Salvadori, 2003; Favre et al.”
Rectangular Patchwork for Bivariate Copulas and Tail Dependence (2009, background): “Relevant applications of this fact are provided, for instance, in finance (see Cherubini et al., 2004; Malevergne and Sornette, 2006; McNeil et al., 2005) and in hydrology (see Salvadori et al., 2007).”
Distorted Copulas: Constructions and Tail Dependence (2010, methodology): “For an introduction to copula theory and some of its applications, we refer to Schweizer and Sklar (2006), Joe (1997), Nelsen (2006), McNeil, Frey, and Embrechts (2005), Salvadori et al. (2007).”
Multivariate hydrologic design methods under nonstationary conditions and application to engineering practice (2018, methodology): “…by considering three widely used definitions of the exceedance probabilities of the multivariate flood event 1 3 7 15, , ,q v v v , i.e., the OR, AND and Kendall cases (Favre et al., 2004; Salvadori et al., 2007; Salvadori and De Michele, 2010; Vandenberghe et al., 2011; Salvadori et al., 2016).”
Increased probability of compound long-duration dry and hot events in Europe during summer (1950–2013) (2019, unknown): “The bivariate RP of an event exceeding Dq and Mq is then estimated as (Salvadori et al 2007): T D M u u C u u , 1 , , 3q q E D M D Mq q q q m = - - + ( ) ( ) ( ) where N NE Y Em = is the average inter-arrival time of events whereD andM jointly exceed the thresholds dsel bi andmsel bi , and u F DD D…”
Modeling the spatial dependence of floods using the Fisher copula (2019, background): “…2008), which implies tail symmetry For a theoretical introduction to copulas, the reader is referred to Durante and Sempi (2015), Joe (2014), or Nelsen (2005), and for an introduction with an engineering focus to Genest and Favre (2007), Salvadori et al. (2007), and Salvadori and De Michele (2007 .”
Bivariate drought frequency analysis using the copula method (2012, methodology): “Salvadori et al. (2007) presented several environmental and geophysical examples by discussing univariate and multivariate extreme value theory, the copula approach, and the relationships between these two research areas.”
Multivariate assessment of droughts: Frequency analysis and dynamic return period (2013, methodology): “Note that aThe ‘‘Clayton,’’ ‘‘Gumbel,’’ and ‘‘Frank’’ labels denote the corresponding families of Archimedean 2-copulas [Nelsen, 2006; Salvadori et al., 2007]; the labels ‘‘Mix[AB]’’ denote a convex mixture C of the two families A and B indicated (i.e., C ¼ Aþ 1 ð ÞB with 2 0; 1½ ); the labels ‘‘X[A”