On concordance measures for discrete data and dependence properties of Poisson model.
Bouezmarni, Taoufik, Mesfioui, Mhamed, Tajar, Abdelouahid (2009)
Journal of Probability and Statistics
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Displaying similar documents to “Dependence Structure of some Bivariate Distributions”
On concordance measures for discrete data and dependence properties of Poisson model.
Extreme distribution functions of copulas
Manuel Úbeda-Flores (2008)
Kybernetika
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In this paper we study some properties of the distribution function of the random variable C(X,Y) when the copula of the random pair (X,Y) is M (respectively, W) – the copula for which each of X and Y is almost surely an increasing (respectively, decreasing) function of the other –, and C is any copula. We also study the distribution functions of M(X,Y) and W(X,Y) given that the joint distribution function of the random variables X and Y is any copula.
On a general structure of the bivariate FGM type distributions
Sayed Mohsen Mirhosseini, Mohammad Amini, Ali Dolati (2015)
Applications of Mathematics
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In this paper, we study a general structure for the so-called Farlie-Gumbel-Morgenstern (FGM) family of bivariate distributions. Through examples we show how to use the proposed structure to study dependence properties of the FGM type distributions by a general approach.
Operations on distribution functions not derivable from operations on random variables
B. Schweizer, A. Sklar (1974)
Studia Mathematica
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Evaluating the bivariate compound generalized Poisson distribution.
Vernic, Raluca (2001)
Analele Ştiinţifice ale Universităţii “Ovidius" Constanţa. Seria: Matematică
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Bivariate extension of the Pickands–Balkema–de Haan theorem
Mario V. Wüthrich (2004)
Annales de l'I.H.P. Probabilités et statistiques
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Random variables, joint distribution functions, and copulas
Abe Sklar (1973)
Kybernetika
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Bounds for distribution functions of sums of squares and radial errors.
Nelsen, Roger B., Schweizer, Berthold (1991)
International Journal of Mathematics and Mathematical Sciences
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A model for proportions with medical applications
Saralees Nadarajah (2007)
Applicationes Mathematicae
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Data that are proportions arise most frequently in biomedical research. In this paper, the exact distributions of R = X + Y and W = X/(X+Y) and the corresponding moment properties are derived when X and Y are proportions and arise from the most flexible bivariate beta distribution known to date. The associated estimation procedures are developed. Finally, two medical data sets are used to illustrate possible applications.