Bivariate flood frequency analysis: Part 1. Determination of marginals by parametric and nonparametric techniques

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Bivariate frequency analysis of floods using a diffusion based kernel density estimator (2013, methodology): “…been extensively used for multivariate flood frequency analysis (FFA) in hydrology [e.g., Favre et al., 2004; Grimaldi and Serinaldi, 2006; Zhang and Singh, 2007a, 2007b; Genest et al., 2007; Karmakar and Simonovic, 2008, 2009; Chebana and Ouarda, 2009; Klein et al., 2010, and references therein].”
Comparison between the peaks-over-threshold method and the annual maximum method for flood frequency analysis (2014, methodology): “This type of AIC test was used by Karmakar and Simonovic (2008, 2009).”
Bivariate flood frequency analysis using the copula function: a case study of the Litija station on the Sava River (2015, background): “In contrast, Karmakar and Simonovic (2008, 2009) and Reddy and Ganguli (2012b) obtained higher correlation values for the pair Q-V.”
Assessing the hydrodynamic boundary conditions for risk analyses in coastal areas: a multivariate statistical approach based on Copula functions (2012, methodology): “Here, for both of the parametersS andF the following Gaussian (or Normal) Kernel Density FunctionK(x) is applied (see e.g. Karmakar and Simonovic, 2008): K(x) = (2π)−1/2e(x 2)/2, with ∞∫ −∞ K(x)dx = 1 (1) To calculate joint probabilities from the marginal distributions, different Copula functions…”