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Empirical processes of multidimensional systems with multiple mixing properties

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  • Dehling, Herold
  • Durieu, Olivier

Abstract

We establish a multivariate empirical process central limit theorem for stationary -valued stochastic processes (Xi)i>=1 under very weak conditions concerning the dependence structure of the process. As an application, we can prove the empirical process CLT for ergodic torus automorphisms. Our results also apply to Markov chains and dynamical systems having a spectral gap on some Banach space of functions. Our proof uses a multivariate extension of the techniques introduced by Dehling et al. (2009) [9] in the univariate case. As an important technical ingredient, we prove a 2pth moment bound for partial sums in multiple mixing systems.

Suggested Citation

  • Dehling, Herold & Durieu, Olivier, 2011. "Empirical processes of multidimensional systems with multiple mixing properties," Stochastic Processes and their Applications, Elsevier, vol. 121(5), pages 1076-1096, May.
    • Handle: RePEc:eee:spapps:v:121:y:2011:i:5:p:1076-1096
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    References listed on IDEAS

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    1. Dedecker, Jérôme & Prieur, Clémentine, 2007. "An empirical central limit theorem for dependent sequences," Stochastic Processes and their Applications, Elsevier, vol. 117(1), pages 121-142, January.
    2. Dehling, Herold & Durieu, Olivier & Volny, Dalibor, 2009. "New techniques for empirical processes of dependent data," Stochastic Processes and their Applications, Elsevier, vol. 119(10), pages 3699-3718, October.
    3. Doukhan, Paul & Louhichi, Sana, 1999. "A new weak dependence condition and applications to moment inequalities," Stochastic Processes and their Applications, Elsevier, vol. 84(2), pages 313-342, December.
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    1. Durieu, Olivier, 2013. "Empirical processes of iterated maps that contract on average," Statistics & Probability Letters, Elsevier, vol. 83(11), pages 2454-2458.
    2. Bucher, Axel & Segers, Johan & Volgushev, Stanislav, 2013. "When uniform weak convergence fails: empirical processes for dependence functions via epi- and hypographs," LIDAM Discussion Papers ISBA 2013019, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. Olivier Durieu & Marco Tusche, 2014. "An Empirical Process Central Limit Theorem for Multidimensional Dependent Data," Journal of Theoretical Probability, Springer, vol. 27(1), pages 249-277, March.
    4. Bücher, Axel & Volgushev, Stanislav, 2013. "Empirical and sequential empirical copula processes under serial dependence," Journal of Multivariate Analysis, Elsevier, vol. 119(C), pages 61-70.

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