Copulas, m-dependence, and Markov chains

Abstract We embrace the notions of m -dependence and Markov chains in the setup of copulas to derive new families of copulas that generate m -dependent Markov chains. We characterize, in general, the copula of an m -dependent Markov chain, providing necessary and sufficient conditions for a copula to generate m -dependent Markov chains using the theory of nilpotent operators on separable Hilbert spaces. We also provide central limit theorems for estimates of the population mean and variance of functions of the m -dependent Markov chains.

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Journal
Test
Published
2026-02-21
DOI
https://doi.org/10.1007/s11749-026-01003-0
Primary Topic
Probability and Risk Models
Type
article
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article

Copulas, m-dependence, and Markov chains

Martial Longla
Test
Probability and Risk Models
article

Copulas, m-dependence, and Markov chains

Martial Longla
article en

Abstract

Abstract We embrace the notions of m -dependence and Markov chains in the setup of copulas to derive new families of copulas that generate m -dependent Markov chains. We characterize, in general, the copula of an m -dependent Markov chain, providing necessary and sufficient conditions for a copula to generate m -dependent Markov chains using the theory of nilpotent operators on separable Hilbert spaces. We also provide central limit theorems for estimates of the population mean and variance of functions of the m -dependent Markov chains.

Test
University of Mississippi (US)
Reduced inequalities
Openalex Percentile: Top 53%
Probability and Risk Models
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