Results 51 to 60 of about 355 (84)
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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Successive Standardization of Rectangular Arrays
, 2012 In this note we illustrate and develop further with mathematics and examples, the work on successive standardization (or normalization) that is studied earlier by the same authors in Olshen and Rajaratnam (2010) and Olshen and Rajaratnam (2011). Thus, we
Olshen, Richard A., Rajaratnam, Bala
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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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Checkerboard copula defined by sums of random variables
Dependence Modeling, 2020 We consider the problem of finding checkerboard copulas for modeling multivariate distributions. A checkerboard copula is a distribution with a corresponding density defined almost everywhere by a step function on an m-uniform subdivision of the unit ...
Kuzmenko Viktor +2 more
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Dependence Modeling, 2021 The paper investigates the Hoeffding–Sobol decomposition of homogeneous co-survival functions. For this class, the Choquet representation is transferred to the terms of the functional decomposition, and in addition to their individual variances, or to ...
Mercadier Cécile, Ressel Paul
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On convergence of associative copulas and related results
Dependence Modeling, 2021 Triggered by a recent article establishing the surprising result that within the class of bivariate Archimedean copulas 𝒞ar different notions of convergence - standard uniform convergence, convergence with respect to the metric D1, and so-called weak ...
Kasper Thimo M. +2 more
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Geometry of the faithfulness assumption in causal inference
, 2013 Many algorithms for inferring causality rely heavily on the faithfulness assumption. The main justification for imposing this assumption is that the set of unfaithful distributions has Lebesgue measure zero, since it can be seen as a collection of ...
Bühlmann, Peter +3 more
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New results on perturbation-based copulas
Dependence Modeling, 2021 A prominent example of a perturbation of the bivariate product copula (which characterizes stochastic independence) is the parametric family of Eyraud-Farlie-Gumbel-Morgenstern copulas which allows small dependencies to be modeled.
Saminger-Platz Susanne +4 more
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On a class of norms generated by nonnegative integrable distributions
Dependence Modeling, 2019 We show that any distribution function on ℝd with nonnegative, nonzero and integrable marginal distributions can be characterized by a norm on ℝd+1, called F-norm. We characterize the set of F-norms and prove that pointwise convergence of a sequence of F-
Falk Michael, Stupfler Gilles
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Dependence Modeling, 2021 As a motivating problem, we aim to study some special aspects of the marginal distributions of the order statistics for exchangeable and (more generally) for minimally stable non-negative random variables T1, ..., Tr. In any case, we assume that T1, ...,
Foschi Rachele +2 more
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