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Functional CLT for nonstationary strongly mixing processes

Author

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  • Merlevède, Florence
  • Peligrad, Magda

Abstract

This paper deals with the functional central limit theorem for non-stationary dependent sequences of random variables satisfying the Lindeberg condition. The dependence condition which we impose is known under the name of weak strong mixing condition. It is satisfied by a large class of dependent random variables, including functions of strongly mixing or α-dependent Markov chains.

Suggested Citation

  • Merlevède, Florence & Peligrad, Magda, 2020. "Functional CLT for nonstationary strongly mixing processes," Statistics & Probability Letters, Elsevier, vol. 156(C).
    • Handle: RePEc:eee:stapro:v:156:y:2020:i:c:s0167715219302275
    DOI: 10.1016/j.spl.2019.108581
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    Cited by:

    1. Hafouta, Yeor, 2023. "Convergence rates in the functional CLT for α-mixing triangular arrays," Stochastic Processes and their Applications, Elsevier, vol. 161(C), pages 242-290.
    2. Longla, Martial & Muia Nthiani, Mathias & Djongreba Ndikwa, Fidel, 2022. "Dependence and mixing for perturbations of copula-based Markov chains," Statistics & Probability Letters, Elsevier, vol. 180(C).
    3. Zdeněk Hlávka & Marie Hušková & Simos G. Meintanis, 2020. "Change-point methods for multivariate time-series: paired vectorial observations," Statistical Papers, Springer, vol. 61(4), pages 1351-1383, August.

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