English

A sharp uniform bound for the distribution of sums of Bernoulli trials

Probability 2019-02-20 v4 Combinatorics

Abstract

In this note we establish a uniform bound for the distribution of a sum Sn=X1++XnS_n=X_1+\cdots+X_n of independent non-homogeneous Bernoulli trials. Specifically, we prove that σnP(Sn ⁣= ⁣j)η\sigma_n \mathbb{P}(S_n\!=\!j)\leq\eta where σn\sigma_n denotes the standard deviation of SnS_n and η\eta is a universal constant. We compute the best possible constant η0.4688\eta\sim 0.4688 and we show that the bound also holds for limits of sums and differences of Bernoullis, including the Poisson laws which constitute the worst case and attain the bound. We also investigate the optimal bounds for nn and jj fixed. An application to estimate the rate of convergence of Mann's fixed point iterations is presented.

Keywords

Cite

@article{arxiv.0806.2350,
  title  = {A sharp uniform bound for the distribution of sums of Bernoulli trials},
  author = {Jean-Bernard Baillon and Roberto Cominetti and José Vaisman},
  journal= {arXiv preprint arXiv:0806.2350},
  year   = {2019}
}

Comments

This paper is a revised version of a previous article