Results 21 to 30 of about 71 (62)

Measures of concordance determined by D4‐invariant copulas

open access: yesInternational 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
wiley   +1 more source

Dependence modeling in stochastic frontier analysis

open access: yesDependence Modeling, 2022
This review covers several of the core methodological and empirical developments surrounding stochastic frontier models that incorporate various new forms of dependence.
Mamonov Mikhail E.   +2 more
doaj   +1 more source

Characterizations of multinomial distributions based on conditional distributions

open access: yesInternational 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

Technical and allocative inefficiency in production systems: a vine copula approach

open access: yesDependence Modeling, 2022
Modeling the error terms in stochastic frontier models of production systems requires multivariate distributions with certain characteristics. We argue that canonical vine copulas offer a natural way to model the pairwise dependence between the two main ...
Zhai Jian, James Robert, Prokhorov Artem
doaj   +1 more source

A characterization of matrix variate normal distribution

open access: yesInternational 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
wiley   +1 more source

On partially Schur-constant models and their associated copulas

open access: yesDependence Modeling, 2021
Schur-constant vectors are used to model duration phenomena in various areas of economics and statistics. They form a particular class of exchangeable vectors and, as such, rely on a strong property of symmetry.
Lefèvre Claude
doaj   +1 more source

Dispersive order comparisons on extreme order statistics from homogeneous dependent random vectors

open access: yesDependence Modeling, 2021
In this paper, we investigate sufficient conditions for preservation property of the dispersive order for the smallest and largest order statistics of homogeneous dependent random vectors.
Mesfioui Mhamed, Trufin Julien
doaj   +1 more source

Some functionals for copulas

open access: yesInternational 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

open access: yesDependence 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
doaj   +1 more source

On the asymptotic covariance of the multivariate empirical copula process

open access: yesDependence 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
doaj   +1 more source

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