Results 11 to 20 of about 355 (84)
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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A Limit Theorem for Copulas [PDF]
, 2005 We characterize convergence of a sequence of d-dimensional random vectors by convergence of the one-dimensional margins and of the copula. The result is applied to the approximation of portfolios modelled by t-copulas with large degrees of freedom, and ...
Lindner, Alexander M. +1 more
core +2 more sources
Bayesian estimation of generalized partition of unity copulas
Dependence Modeling, 2020 This paper proposes a Bayesian estimation algorithm to estimate Generalized Partition of Unity Copulas (GPUC), a class of nonparametric copulas recently introduced by [18].
Masuhr Andreas, Trede Mark
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Measures of concordance determined by D4‐invariant copulas
International Journal of Mathematics and Mathematical Sciences, Volume 2004, Issue 70, Page 3867-3875, 2004., 2004 A continuous random vector (X, Y) uniquely determines a copula C : [0, 1] 2 → [0, 1] such that when the distribution functions of X and Y are properly composed into C, the joint distribution function of (X, Y) results. A copula is said to be D4‐invariant if its mass distribution is invariant with respect to the symmetries of the unit square.
H. H. Edwards +2 more
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Characterizations of multinomial distributions based on conditional distributions
International Journal of Mathematics and Mathematical Sciences, Volume 19, Issue 3, Page 595-602, 1996., 1994 Several characterizations of the joint multinomial distribution of two discrete random vectors are derived assuming conditional multinomial distributions.
Khoan T. Dinh +2 more
wiley +1 more source
A characterization of matrix variate normal distribution
International Journal of Mathematics and Mathematical Sciences, Volume 17, Issue 2, Page 341-346, 1994., 1993 The joint normality of two random vectors is obtained based on normal conditional with linear regression and constant covariance matrix of each vector given the value of the other without assuming the existence of the joint density. This result is applied to a characterization of matrix variate normal distribution.
Khoan T. Dinh, Truc T. Nguyen
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Dependence Modeling, 2020 The use of the exponential distribution and its multivariate generalizations is extremely popular in lifetime modeling. Freund’s bivariate exponential model (1961) is based on the idea that the remaining lifetime of any entity in a bivariate system is ...
Guzmics Sándor, Pflug Georg Ch.
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International Journal of Mathematics and Mathematical Sciences, Volume 14, Issue 1, Page 45-53, 1991., 1990 In this paper we study some functionals operating on the set of the n‐copulas defined on [0, 1] n. Conditions under which such functionals are well defined are determined and some counterexamples are described. The study of the fixed points (n‐copulas) for these functionals is also considered, and, finally, some open problems are presented.
C. Alsina, A. Damas, J. J. Quesada
wiley +1 more source
Maximum asymmetry of copulas revisited
Dependence Modeling, 2018 Motivated by the nice characterization of copulas A for which d∞(A, At) is maximal as established independently by Nelsen [11] and Klement & Mesiar [7], we study maximum asymmetry with respect to the conditioning-based metric D1 going back to Trutschnig [
Kamnitui Noppadon +2 more
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Multivariate radial symmetry of copula functions: finite sample comparison in the i.i.d case
Dependence Modeling, 2021 Given a d-dimensional random vector X = (X1, . . ., Xd), if the standard uniform vector U obtained by the component-wise probability integral transform (PIT) of X has the same distribution of its point reflection through the center of the unit hypercube,
Billio Monica +2 more
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