1985
DOI: 10.1007/bfb0074964
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A maximal law of the iterated logarithm for operator-normalized stochastically compact partial sums of i.i.d. random vectors

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Cited by 5 publications
(9 citation statements)
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“…This is the analogue of the known law of the iterated logarithm (L.I.L) for operator stable laws on finite dimensional vector spaces proved in [17,Chapter 5,Theorem]. Recently Neuenschwander and the author [14] proved a related result for the center part of stable measures on the Heisenberg group.…”
Section: Introductionmentioning
confidence: 73%
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“…This is the analogue of the known law of the iterated logarithm (L.I.L) for operator stable laws on finite dimensional vector spaces proved in [17,Chapter 5,Theorem]. Recently Neuenschwander and the author [14] proved a related result for the center part of stable measures on the Heisenberg group.…”
Section: Introductionmentioning
confidence: 73%
“…In [2] it is proved a version of Ottaviani's maximal inequality on measurable groups. We will prove another Ottaviani type maximal inequality and a maximal inequality analogues to [4] and then follow the method of proof presented in [3] and [17].…”
Section: Introductionmentioning
confidence: 99%
“…It is also interesting to compare the following result with the stable ease considered in [18]. It is also interesting to compare the following result with the stable ease considered in [18].…”
Section: Lil On Vector Spacesmentioning
confidence: 85%
“…It follows from the theorem in [12] Since log log[c, d ~ log n as n ---+ oo and since in the case of operator semistable laws one considers the subsequence S[~,] of S,~, it turns out that this is the appropriate generalization of the corresponding result of [18] for operator stable laws. It follows from the theorem in [12] Since log log[c, d ~ log n as n ---+ oo and since in the case of operator semistable laws one considers the subsequence S[~,] of S,~, it turns out that this is the appropriate generalization of the corresponding result of [18] for operator stable laws.…”
Section: Lil On Vector Spacesmentioning
confidence: 97%
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