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Self-Normalized Weak Invariance Principle for Mixing Sequences

Author

Listed:
  • Raluca Balan

    (University of Ottawa, LRSP)

  • Kulik

    (Wroclaw University and University of Ottawa)

Abstract

In this article we give a necessary and su±cient condition for a selfnormalized weak invariance principle, in the case of a strictly stationary Á-mixing sequence fXjgj¸1. This is obtained under the assumptions that the function L(x) = EX2 1 1fjX1·xg is slowly varying at 1 and the mixing coe±cients satisfy Á1=2(n)

Suggested Citation

  • Raluca Balan & Kulik, 2005. "Self-Normalized Weak Invariance Principle for Mixing Sequences," RePAd Working Paper Series lrsp-TRS417, Département des sciences administratives, UQO.
    • Handle: RePEc:pqs:wpaper:082006
    as

    Download full text from publisher

    File URL: http://www.repad.org/ca/on/lrsp/TRS417.pdf
    File Function: First version, 2005
    Download Restriction: no
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    References listed on IDEAS

    as
    1. Shao, Q. M., 1995. "Strong Approximation Theorems for Independent Random Variables and Their Applications," Journal of Multivariate Analysis, Elsevier, vol. 52(1), pages 107-130, January.
    2. Shao, Qi-Man, 1993. "Almost sure invariance principles for mixing sequences of random variables," Stochastic Processes and their Applications, Elsevier, vol. 48(2), pages 319-334, November.
    3. Rackauskas, Alfredas & Suquet, Charles, 2001. "Invariance principles for adaptive self-normalized partial sums processes," Stochastic Processes and their Applications, Elsevier, vol. 95(1), pages 63-81, September.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Kulik, Rafal, 2006. "Limit theorems for self-normalized linear processes," Statistics & Probability Letters, Elsevier, vol. 76(18), pages 1947-1953, December.

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    More about this item

    Keywords

    Self-normalized; weak invariance principle; mixing sequences.;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General

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