Results 1 to 10 of about 51 (51)
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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Dependence Modeling, 2023 Working with shuffles, we establish a close link between Kendall’s τ\tau , the so-called length measure, and the surface area of bivariate copulas and derive some consequences.
Sánchez Juan Fernández +1 more
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A nonparametric test for comparing survival functions based on restricted distance correlation
Dependence Modeling, 2023 In this article, we propose an omnibus test for comparing two survival functions under non-proportional hazards. The test statistic is based on a product-limit estimate of the restricted distance correlation, which is closely related to the L2{L}_{2 ...
Zhang Qingyang
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Polynomial bivariate copulas of degree five: characterization and some particular inequalities
Dependence Modeling, 2021 Bivariate polynomial copulas of degree 5 (containing the family of Eyraud-Farlie-Gumbel-Morgenstern copulas) are in a one-to-one correspondence to certain real parameter triplets (a, b, c), i.e., to some set of polynomials in two variables of degree 1: p(
Šeliga Adam +5 more
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Weighted Entropic Copula from Preliminary Knowledge of Dependence
Analele Stiintifice ale Universitatii Ovidius Constanta: Seria Matematica, 2018 This paper introduces a weighted entropic copula from preliminary knowledge of dependence. Considering a copula with common distribution we formulate the weighted entropy dependence model (WMEC).
Panait Ioana
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Individualised recovery trajectories of patients with impeded mobility, using distance between probability distributions of learnt graphs [PDF]
MSC: primary, 60-XX; secondary, 05C12; 62H20.Patients who are undergoing physical rehabilitation, benefit from feedback that follows from reliable assessment of their cumulative performance attained at a given time. In this paper, we provide a method for
Zhang, C, Chakrabarty, D, Grosan, C
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Continuous displacement interpolation between checkerboard copulas
Dependence ModelingThis paper presents a displacement-like interpolation method between any two given checkerboard copulas. This interpolation is close to the geodesic connecting the two checkerboard copulas in the L 2-Wasserstein space, which, however, leaves the copula ...
Grothe Oliver, Luo Na
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Fast estimation of Kendall's Tau and conditional Kendall's Tau matrices under structural assumptions
Dependence ModelingKendall’s tau and conditional Kendall’s tau matrices are multivariate (conditional) dependence measures between the components of a random vector. For large dimensions, available estimators are computationally expensive and can be improved by averaging ...
van der Spek Rutger, Derumigny Alexis
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A multivariate version of Gini's rank association coefficient
Primary 62H05, Secondary 62H20, Copulas, Gini's coefficient, Multivariate association,
Javad Behboodian +2 more
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Blomqvist’s beta, Copula, Tail dependence, Asymptotic normality, Empirical copula, Asymptotic efficiency, Primary 62H20, Primary 62G20, Secondary 62G30, Secondary 62H10,
Friedrich Schmid, Rafael Schmidt
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