Results 31 to 40 of about 119 (106)
On the asymptotic covariance of the multivariate empirical copula process
Dependence Modeling, 2019 Genest and Segers (2010) gave conditions under which the empirical copula process associated with a random sample from a bivariate continuous distribution has a smaller asymptotic covariance than the standard empirical process based on a random sample ...
Genest Christian +2 more
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Dependence Modeling, 2020 We first review an approach that had been developed in the past years to introduce concepts of “bivariate ageing” for exchangeable lifetimes and to analyze mutual relations among stochastic dependence, univariate ageing, and bivariate ageing.
Nappo Giovanna, Spizzichino Fabio
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A topological proof of Sklar’s theorem in arbitrary dimensions
Dependence Modeling, 2022 Copulas are appealing tools in multivariate probability theory and statistics. Nevertheless, the transfer of this concept to infinite dimensions entails some nontrivial topological and functional analytic issues, making a deeper theoretical understanding
Benth Fred Espen +2 more
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Stable tail dependence functions – some basic properties
Dependence Modeling, 2022 We prove some important properties of the extremal coefficients of a stable tail dependence function (“STDF”) and characterise logistic and some related STDFs.
Ressel Paul
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New copulas based on general partitions-of-unity (part III) — the continuous case
Dependence Modeling, 2019 In this paper we discuss a natural extension of infinite discrete partition-of-unity copulas which were recently introduced in the literature to continuous partition of copulas with possible applications in risk management and other fields.
Pfeifer Dietmar +3 more
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Maximal asymmetry of bivariate copulas and consequences to measures of dependence
Dependence Modeling, 2022 In this article, we focus on copulas underlying maximal non-exchangeable pairs (X,Y)\left(X,Y) of continuous random variables X,YX,Y either in the sense of the uniform metric d∞{d}_{\infty } or the conditioning-based metrics Dp{D}_{p}, and analyze their ...
Griessenberger Florian +1 more
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Copulas, stable tail dependence functions, and multivariate monotonicity
Dependence Modeling, 2019 For functions of several variables there exist many notions of monotonicity, three of them being characteristic for resp. distribution, survival and co-survival functions. In each case the “degree” of monotonicity is just the basic one of a whole scale.
Ressel Paul
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Dependence Modeling, 2019 We study the dynamics of the family of copulas {Ct}t≥0 of a pair of stochastic processes given by stochastic differential equations (SDE). We associate to it a parabolic partial differential equation (PDE). Having embedded the set of bivariate copulas in
Jaworski Piotr
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On the lower bound of Spearman’s footrule
Dependence Modeling, 2019 Úbeda-Flores showed that the range of multivariate Spearman’s footrule for copulas of dimension d ≥ 2 is contained in the interval [−1/d, 1], that the upper bound is attained exclusively by the upper Fréchet-Hoeffding bound, and that the lower bound is ...
Fuchs Sebastian, McCord Yann
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Symmetry of functions and exchangeability of random variables [PDF]
Copula, Exchangeability, Symmetry, Sobolev space, 60B10, 60E05, 62H05,
Karl Siburg, Pavel Stoimenov
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