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Limit theorems for some functionals with heavy tails of adiscrete time Markov chain

Published online by Cambridge University Press:  08 October 2014

Patrick Cattiaux  and
Mawaki Manou-Abi
Patrick Cattiaux
Affiliation:
Institut de Mathématiques de Toulouse. CNRS UMR 5219. Université Paul Sabatier, 118 route de Narbonne, 31062 Toulouse cedex 09, France. [email protected]; [email protected]
Mawaki Manou-Abi
Affiliation:
Institut de Mathématiques de Toulouse. CNRS UMR 5219. Université Paul Sabatier, 118 route de Narbonne, 31062 Toulouse cedex 09, France. [email protected]; [email protected]
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Abstract

Consider an irreducible, aperiodic and positive recurrent discrete time Markov chain(Xn,n ≥0) with invariant distribution μ. We shall investigate thelong time behaviour of some functionals of the chain, in particular the additivefunctional \hbox{$S_{n}=\sum_{i=1}^{n}f(X_{i})$}Sn=∑i=1nf(Xi) for a possibly non square integrable functionf. To thisend we shall link ergodic properties of the chain to mixing properties, extending knownresults in the continuous time case. We will then use existing results of convergence tostable distributions, obtained in [M. Denker and A. Jakubowski, Stat. Probab.Lett. 8 (1989) 477–483; M. Tyran-Kaminska, StochasticProcess. Appl. 120 (2010) 1629–1650; D. Krizmanic, Ph.D. thesis(2010); B. Basrak, D. Krizmanic and J. Segers, Ann. Probab. 40(2012) 2008–2033] for stationary mixing sequences. Contrary to the usualL^2L2 frameworkstudied in [P. Cattiaux, D. Chafai and A. Guillin, ALEA, Lat. Am. J. Probab. Math.Stat. 9 (2012) 337–382], where weak forms of ergodicity aresufficient to ensure the validity of the Central Limit Theorem, we will need here strongergodic properties: the existence of a spectral gap, hyperboundedness (orhypercontractivity). These properties are also discussed. Finally we give explicitexamples.

Keywords

Markov chainsstable limit theoremsstable distributionslog-Sobolev inequalityadditive functionalsfunctional limit theorem
Type
Research Article
Information
ESAIM: Probability and Statistics , Volume 18 , 2014 , pp. 468 - 482
Copyright
© EDP Sciences, SMAI 2014

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