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arXiv 1901.04865math.PR
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基于累积量的Rosenthal型矩估计

Moment estimates of Rosenthal type via cumulants

Peter Eichelsbacher, Lukas Knichel

摘要:

本文的目的是建立一类相当一般的随机变量的Rosenthal型矩估计,它们满足累积量的一定界。我们考虑随机变量序列满足中心极限定理,并估计相应的时刻的收敛速度的时刻的一个标准的正态分布变量。我们讨论的随机对象的例子包括那些依赖图或加权依赖图编码依赖结构的对象。我们给出了$G(n,p)$和$G(n,m)$型Erdens-Rényi随机图的子图计数统计量、均匀随机对划分中的交叉和$d$维Ising模型中的自旋的应用.此外,我们还证明了随机矩阵理论中出现的某些统计量的矩估计,即随机酉矩阵的特征多项式以及某些随机矩阵系综的行列式。我们增加估计的$p(n)$维体积的单形与$p(n)+1$点分布在${\mathbb R}^n$根据特殊的分布,因为它是强连接到革兰氏矩阵合奏。

英文摘要:

The purpose of the present paper is to establish moment estimates of Rosenthal type for a rather general class of random variables satisfying certain bounds on the cumulants. We consider sequences of random variables which satisfy a central limit theorem and estimate the speed of convergence of the corresponding moments to the moments of a standard normally distributed variable. The examples of random objects we discuss include those where a dependency graphs or a weighted dependency graph encodes the dependency structure. We give applications to subgraph-counting statistics in Erdős-Rényi random graphs of type $G(n,p)$ and $G(n,m)$, crossings in uniform random pair partitions and spins in the $d$-dimensional Ising model. Moreover, we prove moment estimates for certain statistics appearing in random matrix theory, namely characteristic polynomials of random unitary matrices as well as the determinants of certain random matrix ensembles. We add estimates for the $p(n)$-dimensional volume of the simplex with $p(n)+1$ points in ${\mathbb R}^n$ distributed according to special distributions, since it is strongly connected to Gram matrix ensembles.

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