English

Small Deviations of Sums of Independent Random Variables

Probability 2018-04-06 v1

Abstract

A well-known discovery of Feige's is the following: Let X1,,XnX_1, \ldots, X_n be nonnegative independent random variables, with E[Xi]1  i\mathbb{E}[X_i] \leq 1 \;\forall i, and let X=i=1nXiX = \sum_{i=1}^n X_i. Then for any nn, Pr[X<E[X]+1]α>0,\Pr[X < \mathbb{E}[X] + 1] \geq \alpha > 0, for some α1/13\alpha \geq 1/13. This bound was later improved to 1/81/8 by He, Zhang, and Zhang. By a finer consideration of the first four moments, we further improve the bound to approximately .14.14. The conjectured true bound is 1/e.3681/e \simeq .368, so there is still (possibly) quite a gap left to fill.

Keywords

Cite

@article{arxiv.1804.01529,
  title  = {Small Deviations of Sums of Independent Random Variables},
  author = {Brian Garnett},
  journal= {arXiv preprint arXiv:1804.01529},
  year   = {2018}
}

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21 pages