Continuous Bivariate Distributions

By Narayanaswamy Balakrishnan, Chin Diew Lai. 2009

585 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/6944145e26bdf2c5fdeb43186c555d6130589179

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In Artificial Intelligence

Citations in the corpus

Single‐site monthly streamflow simulation using entropy theory (2011, methodology): “[27] There are several techniques that can be employed for the generation of random values from the bivariate distribution, such as the conditional distribution method, the transformation method, the acceptance/rejection method, and the composition method [Johnson, 1987; Balakrishnan and Lai, 2009].”
Entropy–Copula in Hydrology and Climatology (2014, methodology): “…a joint distribution have been proposed and applied, including the kernel density estimation, entropy method, and copulas, to name a few (Kapur 1989; Kotz et al. 2000; Grimaldi and Serinaldi 2006; Nelsen 2006; Serinaldi and Grimaldi 2007; Balakrishnan and Lai 2009; AghaKouchak et al. 2010a,b).”
On the exact region determined by Kendall's τ and Spearman's ρ (2015, background): “s and the interrelation between ˝and ˆhas received much attention also in recent years, in particular concerning the so-called Hutchinson-Lai conjecture (Fredricks and Nelsen, 2007; Hurlimann, 2003; Balakrishnan and Lai, 2009), to the best of the authors’ knowledge the exact ˝-ˆregion , dened by (Cd”
The Bivariate Normal Copula (2009, methodology): “For collections of facts on the bivariate (or multivariate) distribution we refer to the books of Balakrishnan & Lai (2009), of Kotz, Balakrishnan & Johnson (2000), and of Patel & Read (1996), and to the survey article of Gupta (1963a) with its extensive bibliography (Gupta 1963b).”
A copula-based approach to account for dependence in stress-strength models (2013, methodology): “j=0 ( p1 − 1 i )( p2 − 1 j ) (−1) {I(i, j)− (1 +m2p2)I(i, j + 1) −(1 +m1p1)I(i+ 1, j) + (1 +m1p1)(1 +m2p2)I(i+ 1, j + 1)} (7)”
Handling Endogenous Regressors by Joint Estimation Using Copulas (2012, unknown): “In the statistics literature, various copula functions have been studied (see Nelsen 2006 or Balakrishnan and Lai 2009).”