A new tail bound for the sum of bounded independent random variables

Fuente: arXiv
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Main Authors: Loper, Jackson, Regier, Jeffrey
Format: Preprint
Published: 2025
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author Loper, Jackson
Regier, Jeffrey
author_facet Loper, Jackson
Regier, Jeffrey
contents We construct a new tail bound for the sum of independent random variables for situations in which the expected value of the sum is known and each random variable lies within a specified interval, which may be different for each variable. This new bound can be computed by solving a two-dimensional convex optimization problem. Simulations demonstrate that the new bound is often substantially tighter than Hoeffding's inequality for cases in which both bounds are applicable.
format Preprint
id arxiv_https___arxiv_org_abs_2503_17594
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A new tail bound for the sum of bounded independent random variables
Loper, Jackson
Regier, Jeffrey
Probability
Statistics Theory
We construct a new tail bound for the sum of independent random variables for situations in which the expected value of the sum is known and each random variable lies within a specified interval, which may be different for each variable. This new bound can be computed by solving a two-dimensional convex optimization problem. Simulations demonstrate that the new bound is often substantially tighter than Hoeffding's inequality for cases in which both bounds are applicable.
title A new tail bound for the sum of bounded independent random variables
topic Probability
Statistics Theory
url https://arxiv.org/abs/2503.17594