Bivariate return periods via 2-Copulas

By G. Salvadori. 2004

131 citations recorded by the source corpus.

Subfields: Finance, Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/d2c2d5b8fed527096dd72db18d05dec4b26faede

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Citations in the corpus

Risk Assessment of Droughts in Gujarat Using Bivariate Copulas (2012, unknown): “Thus risk (exceedance probability) should be defined in terms of joint behavior of the specific drought events (Salvadori 2004).”
Flood Coincidence Risk Analysis Using Multivariate Copula Functions (2012, methodology): “2007), return-period analysis (Salvadori and De Michele 2004; Salvadori 2004), multivariate simulation (AghaKouchak et al.”
Importance of Tail Dependence in Bivariate Frequency Analysis (2007, methodology): “Recently, several authors have used a modeling based on copulas to sidestep those shortcomings De Michele and Salvadori 2002; Salvadori 2004; Salvadori and De Michele 2004; Favre et al. 2004; Serinaldi et al. 2004; Singh and Zhang 2004a,b; De Michele et al. 2005; Grimaldi et al. 2005; Grimaldi and…”
A stochastic design rainfall generator based on copulas and mass curves (2010, unknown): “Eventually, the secondary return period was proposed as being very useful for design purposes ( Salvadori and De Michele, 2004; Salvadori , 2004; Salvadori et al. , 2007). Unfortunately, this type of return period did not yet find its way to engineering applications, except for some considerations i”
Probabilistic modeling of flood characterizations with parametric and minimum information pair-copula model (2016, methodology): “For multivariate case, in which the flood variables, D;V ; P exceeds their respective thresholds ðD > d ;V > v ; P > p Þ, the joint return period is computed using inclusive probability (‘‘OR” and ‘‘AND” cases) of all three events, known as primary return periods (Salvadori, 2004).”
Probabilistic assessment of flood risks using trivariate copulas (2012, methodology): “For multivariate case, in which X1, X2…, Xd exceeds their respective thresholds (X1>x1,⋯Xd>xd), the joint return period is computed using inclusive probability (“OR” and “AND” cases) of all three events, known as primary return periods (Salvadori 2004).”
Bivariate flood frequency analysis. Part 2: a copula‐based approach with mixed marginal distributions (2009, background): “Salvadori (2004) investigated several types of possible bivariate events (using ‘AND’ and ‘OR’ cases) and provided explicit analytical formulae of practical interest.”
A comparative copula‐based bivariate frequency analysis of observed and simulated storm events: A case study on Bartlett‐Lewis modeled rainfall (2011, methodology): “In this context, the concept of a secondary return period has emerged as being conceptually more useful for design purposes [Salvadori and De Michele, 2004; Salvadori, 2004; Salvadori et al., 2007; Vandenberghe et al., 2010b].”
On the return period and design in a multivariate framework (2011, background): “As an illustration, consider the two different bivariate dangerous regions constructed in Salvadori (2004); Salvadori and De Michele (2004).”
On the construction of multivariate extreme value models via copulas (2009, methodology): “For a thorough theoretical and practical introduction see, respectively, Joe (1997); Nelsen (2006) and Salvadori et al. (2007). Hereafter, for any integer d > 1, we use the vector notation in R , i.”
Dependence of drivers affects risks associated with compound events (2017, background): “The probability of an event, where both variables exceed a given threshold, is given by (49, 50)”
Multivariate multiparameter extreme value models and return periods: A copula approach (2010, methodology): “Thus, the Kendall’s measure KC is a fundamental tool for introducing a consistent (copula‐based) definition of a return period for multivariate events (see also the discussions by Salvadori [2004] , Salvadori and De Michele [2004], Salvadori et al. [2007], and Durante and Salvadori [2010]).”
Multivariate return periods in hydrology: a critical and practical review focusing on synthetic design hydrograph estimation (2012, methodology): “used by Salvadori and De Michele (2012). 3.4 Design events derived from a copula’s Kendall distribution function Another definition of the bivariate return period is given by Salvadori and De Michele(2004); Salvadori(2004) and Salvadori et al. (2007). Recently, the concept of this bivariate secondar”