Operations on distribution functions not derivable from operations on random variables
B. Schweizer, A. Sklar (1974)
Studia Mathematica
Similarity:
The search session has expired. Please query the service again.
The search session has expired. Please query the service again.
B. Schweizer, A. Sklar (1974)
Studia Mathematica
Similarity:
Manuel Úbeda-Flores (2008)
Kybernetika
Similarity:
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.
Claudi Alsina, Eduard Bonet (1979)
Stochastica
Similarity:
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.
Fabrizio Durante, Radko Mesiar, Carlo Sempi (2008)
Kybernetika
Similarity:
Piotr Mikusinski, Howard Sherwood, Michael D. Taylor (1992)
Stochastica
Similarity:
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...