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An Empirical Process Central Limit Theorem for Multidimensional Dependent Data

Author

Listed:
  • Olivier Durieu

    (Université de Tours)

  • Marco Tusche

    (Ruhr-Universität Bochum)

Abstract

Let $(U_{n}(t))_{t\in\mathbb{R}^{d}}$ be the empirical process associated to an ℝ d -valued stationary process (X i ) i≥0. In the present paper, we introduce very general conditions for weak convergence of $(U_{n}(t))_{t\in\mathbb{R}^{d}}$ , which only involve properties of processes (f(X i )) i≥0 for a restricted class of functions $f\in\mathcal{G}$ . Our results significantly improve those of Dehling et al. (Stoch. Proc. Appl. 119(10):3699–3718, 2009) and Dehling and Durieu (Stoch. Proc. Appl. 121(5):1076–1096, 2011) and provide new applications. The central interest in our approach is that it does not need the indicator functions which define the empirical process $(U_{n}(t))_{t\in\mathbb{R}^{d}}$ to belong to the class $\mathcal{G}$ . This is particularly useful when dealing with data arising from dynamical systems or functionals of Markov chains. In the proofs we make use of a new application of a chaining argument and generalize ideas first introduced in Dehling et al. (Stoch. Proc. Appl. 119(10):3699–3718, 2009) and Dehling and Durieu (Stoch. Proc. Appl. 121(5):1076–1096, 2011). Finally we will show how our general conditions apply in the case of multiple mixing processes of polynomial decrease and causal functions of independent and identically distributed processes, which could not be treated by the preceding results in Dehling et al. (Stoch. Proc. Appl. 119(10):3699–3718, 2009) and Dehling and Durieu (Stoch. Proc. Appl. 121(5):1076–1096, 2011).

Suggested Citation

  • 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.
  • Handle: RePEc:spr:jotpro:v:27:y:2014:i:1:d:10.1007_s10959-012-0450-3
    DOI: 10.1007/s10959-012-0450-3
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    References listed on IDEAS

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    1. 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.
    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. 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.
    4. 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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