Random variables, joint distribution functions, and copulas
Abe Sklar (1973)
Kybernetika
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Abe Sklar (1973)
Kybernetika
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Claudi Alsina, Eduard Bonet (1979)
Stochastica
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We study and solve several functional equations which yield necessary and sufficient conditions for the sum of two uniformly distributed random variables to be uniformly distributed.
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.
Piotr Mikusinski, Howard Sherwood, Michael D. Taylor (1992)
Stochastica
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Copulas are functions which join the margins to produce a joint distribution function. A special class of copulas called shuffles of Min is shown to be dense in the collection of all copulas. Each shuffle of Min is interpreted probabilistically. Using the above-mentioned results, it is proved that the joint distribution of any two continuously distributed random variables X and Y can be approximated uniformly, arbitrarily closely by the joint distribution of another pair X* and Y* each...
Nelsen, Roger B., Schweizer, Berthold (1991)
International Journal of Mathematics and Mathematical Sciences
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