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Dependence Measuring from Conditional Variances

Noppadon Kamnitui, Tippawan Santiwipanont, Songkiat Sumetkijakan (2015)

Dependence Modeling

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...

Dynamic dependence ordering for Archimedean copulas and distorted copulas

Arthur Charpentier (2008)

Kybernetika

This paper proposes a general framework to compare the strength of the dependence in survival models, as time changes, i. e. given remaining lifetimes X , to compare the dependence of X given X > t , and X given X > s , where s > t . More precisely, analytical results will be obtained in the case the survival copula of X is either Archimedean or a distorted copula. The case of a frailty based model will also be discussed in details.

El valor difuso esperado con integrales semiconormadas.

Fermín Suárez, Pedro Gil (1986)

Trabajos de Estadística

In this paper we first use the semiconormed fuzzy integrals in order to extend the definition of the fuzzy expected value (F.E.V.) (Kandel, 1979). We generalize some of the properties due to Kandel with a criticism about his purpose of constraining the F.E.V. to be linear. Finally, a necessary and sufficient condition is given in order to guarantee some linearity properties for any semiconormed fuzzy integral.

Equivalent or absolutely continuous probability measures with given marginals

Patrizia Berti, Luca Pratelli, Pietro Rigo, Fabio Spizzichino (2015)

Dependence Modeling

Let (X,A) and (Y,B) be measurable spaces. Supposewe are given a probability α on A, a probability β on B and a probability μ on the product σ-field A ⊗ B. Is there a probability ν on A⊗B, with marginals α and β, such that ν ≪ μ or ν ~ μ ? Such a ν, provided it exists, may be useful with regard to equivalent martingale measures and mass transportation. Various conditions for the existence of ν are provided, distinguishing ν ≪ μ from ν ~ μ.

Currently displaying 81 – 100 of 301