A law of the iterated logarithm for distributions in the generalized domain of attraction of a nondegenerate Gaussian law
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Publication:1062338
DOI10.1007/BF00334190zbMath0572.60011MaRDI QIDQ1062338
Publication date: 1986
Published in: Probability Theory and Related Fields (Search for Journal in Brave)
law of iterated logarithmgeneralized domain of attractionKuelbs-Zinn conditionmoment techniqueoperator-normalization
Probability measures on topological spaces (60B05) Strong limit theorems (60F15) Large deviations (60F10) Convergence of probability measures (60B10) Set functions and measures and integrals in infinite-dimensional spaces (Wiener measure, Gaussian measure, etc.) (28C20) Probability theory on linear topological spaces (60B11) Limit theorems for vector-valued random variables (infinite-dimensional case) (60B12)
Related Items
Moments of distributions attracted to operator-stable laws, A functional law of the iterated logarithm for distributions in the domain of partial attraction of the normal distribution, A law of the iterated logarithm for semistable laws on vector spaces and homogeneous groups
Cites Work
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- Some results on LIL behavior
- The LIL when X is in the domain of attraction of a Gaussian law
- Extreme values and the law of the iterated logarithm
- Moments of distributions attracted to operator-stable laws
- Matrix normalization of sums of random vectors in the domain of attraction of the multivariate normal
- Exponential moments of vector valued random series and triangular arrays
- Some results on the LIL in Banach space with applications to weighted empirical processes
- Kolmogorov's law of the iterated logarithm for Banach space valued random variables
- Some stability results for vector valued random variables
- Some results on the cluster set \(C(\{S_n/a_n\})\) and the LIL
- Toward a universal law of the iterated logarithm
- Toward a universal law of the iterated logarithm, Part II
- Lévy's probability measures on Banach spaces
- Convergence of types in k-space
- The 1971 Rietz Lecture Sums of Independent Random Variables--Without Moment Conditions
