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On dependence structure of copula-based Markov chains

Published online by Cambridge University Press:  10 October 2014

Martial Longla
Martial Longla*
Affiliation:
Department of Mathematics, University of Mississippi, University, MS 38677, USA. longla_m_martial@yahoo.com; mlongla@olemiss.edu
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Abstract

We consider dependence coefficients for stationary Markov chains. We emphasize on someequivalencies for reversible Markov chains. We improve some known results and provide anecessary condition for Markov chains based on Archimedean copulas to be exponentialρ-mixing.We analyse the example of the Mardia and Frechet copula families using small sets.

Keywords

Markov chainscopulamixingreversible processesergodicitysmall sets

Information

Type
Research Article
Information
ESAIM: Probability and Statistics , Volume 18 , 2014 , pp. 570 - 583
Copyright
© EDP Sciences, SMAI 2014

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References

Beare, B.K., Archimedean copulas and temporal dependence. Econ. Theory 28 (2012) 1165–1185. Google Scholar
Beare, B.K., Copulas and Temporal Dependence. Econometrica 78 (2010) 395–410. Google Scholar
R.C. Bradley, Introduction to strong mixing conditions. Vol. 1, 2. Kendrick press (2007).
K. Chan and H. Tong, Chaos: A Statistical Perspective. Springer, New York (2001).
Doukhan, P., Massart, P. and Rio, E., The functional central limit theorem for strongly mixing processes. Ann. Inst. Henri Poincaré, Section B, Tome 30 (1994) 63–82. Google Scholar
Longla, M. and Peligrad, M., Some Aspects of Modeling Dependence in Copula-based Markov chains. J. Multiv. Anal. 111 (2012) 234–240. Google Scholar
Longla, M., Remarks on the speed of convergence of mixing coefficients and applications. Stat. Probab. Lett. 82 (2013) 2439–2445. Google Scholar
R.B. Nelsen, An introduction to copulas. 2nd edition. Springer, New York (2006).