Some results on two-sided LIL behavior
classification
🧮 math.PR
keywords
behaviorinftyresultsequenceanaloguescaseconditionsdealing
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Let {X,X_n;n\geq 1} be a sequence of i.i.d. mean-zero random variables, and let S_n=\sum_{i=1}^nX_i,n\geq 1. We establish necessary and sufficient conditions for having with probability 1, 0<lim sup_{n\to \infty}|S_n|/\sqrtnh(n)<\infty, where h is from a suitable subclass of the positive, nondecreasing slowly varying functions. Specializing our result to h(n)=(\log \log n)^p, where p>1 and to h(n)=(\log n)^r, r>0, we obtain analogues of the Hartman-Wintner LIL in the infinite variance case. Our proof is based on a general result dealing with LIL behavior of the normalized sums {S_n/c_n;n\ge 1}, where c_n is a sufficiently regular normalizing sequence.
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