Dependence and mixing for perturbations of copula-based Markov chains
Statistics Theory
2021-06-11 v1 Probability
Statistics Theory
Abstract
This paper explores the impact of perturbations of copulas on dependence properties of the Markov chains they generate. We use an observation that is valid for convex combinations of copulas to establish sufficient conditions for the mixing coefficients , and some other measures of association. New copula families are derived based on perturbations of copulas and their multivariate analogs for -copulas are provided in general. Several families of copulas can be constructed from the provided framework.
Keywords
Cite
@article{arxiv.2106.05766,
title = {Dependence and mixing for perturbations of copula-based Markov chains},
author = {Martial Longla and Mathias Muia Nthiani and Fidel Djongreba Ndikwa},
journal= {arXiv preprint arXiv:2106.05766},
year = {2021}
}
Comments
13 pages 0 figures