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arXiv 1602.06148math.PRmath.MG
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高斯多面体:一种基于累积量的方法

Gaussian polytopes: a cumulant-based approach

Julian Grote, Christoph Thaele

摘要:

研究了强度测度为$\mathbb{R}^d$上标准高斯测度的倍数的$\mathbb{R}^d$上Poisson点过程的随机凸包.本文基于累积量和Saulis和Statulevičius的一般大偏差理论,提出了一种关于这类高斯多面体的新观点。这导致新的和强大的浓度不等式,矩界,Marcinkiewicz-Zygmund型强大数定律,中心极限定理和适度偏差原则的体积和面数。相应的结果也来自这些关键的几何泛函引起的经验措施,从而照顾他们的空间配置文件。

英文摘要:

The random convex hull of a Poisson point process in $\mathbb{R}^d$ whose intensity measure is a multiple of the standard Gaussian measure on $\mathbb{R}^d$ is investigated. The purpose of this paper is to invent a new viewpoint on these Gaussian polytopes that is based on cumulants and the general large deviation theory of Saulis and Statulevičius. This leads to new and powerful concentration inequalities, moment bounds, Marcinkiewicz-Zygmund-type strong laws of large numbers, central limit theorems and moderate deviation principles for the volume and the face numbers. Corresponding results are also derived for the empirical measures induced by these key geometric functionals, taking thereby care of their spatial profiles.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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