Démonstration élémentaire d'une proposition générale de la théorie des probabilités.
Dependence Measuring from Conditional Variances
A conditional variance is an indicator of the level of independence between two random variables. We exploit this intuitive relationship and define a measure v which is almost a measure of mutual complete dependence. Unsurprisingly, the measure attains its minimum value for many pairs of non-independent ran- dom variables. Adjusting the measure so as to make it invariant under all Borel measurable injective trans- formations, we obtain a copula-based measure of dependence v* satisfying A. Rényi’s...
Desintegration and compact measures.
Désintégration régulière de mesure sans conditions habituelles
Désintégrations réguliéres, tribus fortes, et probalités extrémales
Deux propriétés des ensembles minces (abstraits)
Die Zurückführung einiger in der Wahrscheinlichkeitsrechnung und in der Statistik auftretenden Integrale auf andere allgemeine Integrale
Difference of general integral means.
Discrete marginal problem for complex measures
Duality for generalized events
Dynamic dependence ordering for Archimedean copulas and distorted copulas
This paper proposes a general framework to compare the strength of the dependence in survival models, as time changes, i. e. given remaining lifetimes , to compare the dependence of given , and given , where . More precisely, analytical results will be obtained in the case the survival copula of is either Archimedean or a distorted copula. The case of a frailty based model will also be discussed in details.