An asymptotically optimal bound for the concentration function of a sum of independent integer random variables
Abstract
For a random variable $X$ define $Q(X) = \sup_{x \in \mathbb{R}} \mathbb{P}(X=x)$.
Let $X_1, \dots, X_n$ be independent integer random variables. Suppose $Q(X_i) \le α_i \in (0,1]$ for each $i \in \{1, \dots, n\}$. JuÅ¡keviÄius (2023) conjectured that $Q(X_1 + \dots +X_n) \le Q(Y_1 + \dots+ Y_n)$ where $Y_1, \dots, Y_n$ are independent and $Y_i$ is a random integer variable with $Q(Y_i) =α_i$ that has the smallest variance, i.e. the distribution of $Y_i$ has probabilities $α_i, \dots, α_i, β_i$ or probabilities $β_i, α_i, \dots, α_i$ on some interval of integers, where $0 \le β_i < α_i$. We prove this conjecture asymptotically: i.e., we show that for each $δ> 0$ there is $V_0 = V_0(δ)$ such that if ${\mathrm Var} (\sum Y_i) \ge V_0$ then $Q(\sum X_i) \le (1+δ) Q(\sum Y_i)$.
This implies an analogous asymptotically optimal inequality for concentration at a point when $X_1$, $\dots$, $X_n$ take values in a separable Hilbert space.
Our long and technical argument relies on several non-trivial previous results including an inverse Littlewood--Offord theorem and an approximation in total variation distance of sums of multivariate lattice random vectors by a discretized Gaussian distribution.引用本文复制引用
Valentas Kurauskas.An asymptotically optimal bound for the concentration function of a sum of independent integer random variables[EB/OL].(2026-03-11)[2026-03-13].https://arxiv.org/abs/2603.11043.学科分类
数学
|国家预印本平台
评论