论文标题
Berry-Esseen类型的估计值，具有稀疏依赖图的随机变量
Berry-Esseen-type estimates for random variables with a sparse dependency graph
论文作者
论文摘要
我们使用依赖变换方法在（2，\ infty] $中的顺序$δ\ $Δ\均均匀边界的随机变量的总和中获得浆果 - 类型的界限。我们的界限可改善依赖性图形的跨度依赖性的依赖性，我们的界限是在我们的跨度范围内获得的，我们获得了跨度的依据，我们获得了跨度的依据。以$ l^δ$限制（2，\ infty] $的某些$δ\。
We obtain Berry-Esseen-type bounds for the sum of random variables with a dependency graph and uniformly bounded moments of order $δ\in (2,\infty]$ using a Fourier transform approach. Our bounds improve the state-of-the-art in the regime where the degree of the dependency graph is large. As a Corollary of our results, we obtain a Central Limit Theorem for random variables with a sparse dependency graph that are uniformly bounded in $L^δ$ for some $δ\in(2,\infty]$.
