New results on perturbation-based copulas-Reference-Cited by-同舟云学术

New results on perturbation-based copulas

Published:2021-01-01 Issue:1 Volume:9 Page:347-373
ISSN:2300-2298
Container-title:Dependence Modeling
language:en
Short-container-title:

Author:

Saminger-Platz Susanne¹^ORCID,Kolesárová Anna²^ORCID,Šeliga Adam³^ORCID,Mesiar Radko⁴^ORCID,Klement Erich Peter¹^ORCID

Affiliation:

1. Institute for Mathematical Methods in Medicine and Data Based Modeling , Johannes Kepler University , Linz , Austria

2. Institute of Information Engineering, Automation and Mathematics, Faculty of Chemical and Food Technology , Slovak University of Technology , Bratislava , Slovakia

3. Department of Mathematics and Descriptive Geometry, Faculty of Civil Engineering , Slovak University of Technology , Bratislava , Slovakia

4. Department of Mathematics and Descriptive Geometry, Faculty of Civil Engineering , Slovak University of Technology , Bratislava , Slovakia , and Institute for Research and Applications of Fuzzy Modeling, NSC IT4Innovations , University of Ostrava , Czech Republic

Abstract

Abstract 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. We introduce and discuss several perturbations, some of them perturbing the product copula, while others perturb general copulas. A particularly interesting case is the perturbation of the product based on two functions in one variable where we highlight several special phenomena, e.g., extremal perturbed copulas. The constructions of the perturbations in this paper include three different types of ordinal sums as well as flippings and the survival copula. Some particular relationships to the Markov product and several dependence parameters for the perturbed copulas considered here are also given.

Publisher

Walter de Gruyter GmbH

Subject

Applied Mathematics,Modeling and Simulation,Statistics and Probability

Link

https://www.degruyter.com/document/doi/10.1515/demo-2021-0116/pdf

Reference123 articles.

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