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Random central limit theorem for the linear process generated by a strong mixing process

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  • Lee, Sangyeol

Abstract

This paper considers the random central limit theorem (CLT) for a linear process of which the error process is strong mixing with the associated mixing order satisfying certain regularity conditions. By using the moment inequality of Yokoyama (1980, Corollary 1) we prove that the random CLT holds for the error process, which is a generalization of Réyni (1960) on iid random variables. Based on this result and applying the Beveridge and Nelson decomposition of the linear process (cf. Phillips and Solo, 1993), the random CLT is established for the linear process generated by strong mixing processes.

Suggested Citation

  • Lee, Sangyeol, 1997. "Random central limit theorem for the linear process generated by a strong mixing process," Statistics & Probability Letters, Elsevier, vol. 35(2), pages 189-196, September.
  • Handle: RePEc:eee:stapro:v:35:y:1997:i:2:p:189-196
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    References listed on IDEAS

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    1. Fakhre-Zakeri, Issa & Farshidi, Jamshid, 1993. "A central limit theorem with random indices for stationary linear processes," Statistics & Probability Letters, Elsevier, vol. 17(2), pages 91-95, May.
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    Cited by:

    1. Moon, H.J., 2008. "The functional CLT for linear processes generated by mixing random variables with infinite variance," Statistics & Probability Letters, Elsevier, vol. 78(14), pages 2095-2101, October.

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