# ON THE RATES OF THE ALMOST SURE CONVERGENCE FOR SELF-NORMALIZED LAW OF THE ITERATED LOGARITHM

• Pang, Tian-Xiao (Department of Mathematics Yuquan Campus Zhejiang University)
• 투고 : 2010.03.22
• 발행 : 2011.11.30

#### 초록

Let {$X_i$, $i{\geq}1$} be a sequence of i.i.d. nondegenerate random variables which is in the domain of attraction of the normal law with mean zero and possibly infinite variance. Denote $S_n={\sum}_{i=1}^n\;X_i$, $M_n=max_{1{\leq}i{\leq}n}\;{\mid}S_i{\mid}$ and $V_n^2={\sum}_{i=1}^n\;X_i^2$. Then for d > -1, we showed that under some regularity conditions, $$\lim_{{\varepsilon}{\searrow}0}{\varepsilon}^2^{d+1}\sum_{n=1}^{\infty}\frac{(loglogn)^d}{nlogn}I\{M_n/V_n{\geq}\sqrt{2loglogn}({\varepsilon}+{\alpha}_n)\}=\frac{2}{\sqrt{\pi}(1+d)}{\Gamma}(d+3/2)\sum_{k=0}^{\infty}\frac{(-1)^k}{(2k+1)^{2d+2}}\;a.s.$$ holds in this paper, where If g denotes the indicator function.

#### 과제정보

연구 과제 주관 기관 : National Natural Science Foundation of China, Zhejiang Provincial Natural Science Foundation of China

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