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  • 1 Department of Applied Mathematics, Tongji University Shanghai 200092, P.R. China
  • | 2 School of Mathematics and Informational Statistics, Wonkwang University Ik-San 570-749, South Korea
  • | 3 Mathematical Institute, University of Cologne D-50931 Köln, Germany
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Let X1, X2,… be independent, but not necessarily identically distributed random variables in the domain of attraction of a stable law with index 0<a<2. This paper uses Mn=max 1?i?n|Xi| to establish a self-normalized law of the iterated logarithm (LIL) for partial sums. Similarly self-normalized increments of partial sums are studied as well. In particular, the results of self-normalized sums of Horváth and Shao[9]under independent and identically distributed random variables are extended and complemented. As applications, some corresponding results for self-normalized weighted sums of iid random variables are also concluded.

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Gábor SIMONYI (Rényi Institute of Mathematics)
András STIPSICZ (Rényi Institute of Mathematics)
Géza TÓTH (Rényi Institute of Mathematics) 

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  • Andrew SUK (University of California, San Diego)
  • Zoltán SZABÓ (Princeton University)
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  • Gábor TARDOS (Rényi Institute of Mathematics)
  • Paul WOLLAN (University of Rome "La Sapienza")

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Studia Scientiarum Mathematicarum Hungarica
Language English
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1966
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2021 Volume 58
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ISSN 0081-6906 (Print)
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