Concentration inequalities for strong laws and laws of the iterated logarithm

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Hauptverfasser: Ruf, Johannes, Waudby-Smith, Ian
Format: Preprint
Veröffentlicht: 2025
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author Ruf, Johannes
Waudby-Smith, Ian
author_facet Ruf, Johannes
Waudby-Smith, Ian
contents We derive concentration inequalities for sums of independent and identically distributed random variables that yield non-asymptotic generalizations of several strong laws of large numbers including some of those due to Kolmogorov [1930], Marcinkiewicz and Zygmund [1937], Chung [1951], Baum and Katz [1965], Ruf, Larsson, Koolen, and Ramdas [2023], and Waudby-Smith, Larsson, and Ramdas [2024]. As applications, we derive non-asymptotic iterated logarithm inequalities in the spirit of Darling and Robbins [1967], as well as pathwise (sometimes described as "game-theoretic") analogues of strong laws and laws of the iterated logarithm.
format Preprint
id arxiv_https___arxiv_org_abs_2511_00175
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Concentration inequalities for strong laws and laws of the iterated logarithm
Ruf, Johannes
Waudby-Smith, Ian
Probability
Statistics Theory
We derive concentration inequalities for sums of independent and identically distributed random variables that yield non-asymptotic generalizations of several strong laws of large numbers including some of those due to Kolmogorov [1930], Marcinkiewicz and Zygmund [1937], Chung [1951], Baum and Katz [1965], Ruf, Larsson, Koolen, and Ramdas [2023], and Waudby-Smith, Larsson, and Ramdas [2024]. As applications, we derive non-asymptotic iterated logarithm inequalities in the spirit of Darling and Robbins [1967], as well as pathwise (sometimes described as "game-theoretic") analogues of strong laws and laws of the iterated logarithm.
title Concentration inequalities for strong laws and laws of the iterated logarithm
topic Probability
Statistics Theory
url https://arxiv.org/abs/2511.00175