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Almost sure central limit theorems under minimal conditions

Author

Listed:
  • Berkes, István
  • Csáki, Endre
  • Horváth, Lajos

Abstract

Let X1, X2,... be independent, identically distributed random variables with EX1 = 0, EX12 = 1 and let Sn = [summation operator]k[less-than-or-equals, slant]n Xk. We give nearly optimal criteria for an (unbounded) measurable function f to satisfy the a.s. central limit theorem, i.e., a.s., where [phi] is the standard normal density function.

Suggested Citation

  • Berkes, István & Csáki, Endre & Horváth, Lajos, 1998. "Almost sure central limit theorems under minimal conditions," Statistics & Probability Letters, Elsevier, vol. 37(1), pages 67-76, January.
  • Handle: RePEc:eee:stapro:v:37:y:1998:i:1:p:67-76
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    Citations

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    Cited by:

    1. Ibragimov, Ildar & Lifshits, Mikhail, 1998. "On the convergence of generalized moments in almost sure central limit theorem," Statistics & Probability Letters, Elsevier, vol. 40(4), pages 343-351, November.
    2. Berkes, István & Horváth, Lajos, 2001. "The logarithmic average of sample extremes is asymptotically normal," Stochastic Processes and their Applications, Elsevier, vol. 91(1), pages 77-98, January.
    3. Zuoxiang Peng & Zhongquan Tan & Saralees Nadarajah, 2011. "Almost sure central limit theorem for the products of U-statistics," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 73(1), pages 61-76, January.
    4. Fahrner, Ingo, 2000. "An extension of the almost sure max-limit theorem," Statistics & Probability Letters, Elsevier, vol. 49(1), pages 93-103, August.

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