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arXiv 2008.02272math.PR
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基于非线性可交换对的正规逼近

Normal approximation via non-linear exchangeable pairs

Christian Döbler

摘要:

我们提出了一个新的功能分析方法,斯坦的方法,不需要对手头上,以满足任何近似线性回归属性的可交换对。我们利用这一理论,以获得抽象的正常和伽马逼近的某些功能的Wasserstein距离的界限。此外,我们说明了这种方法的相关性,通过三个实例的情况下,它可以应用:独立随机变量的泛函,有限总体统计和泛函有限群。在独立的情况下,特别是对称的$U$ -统计,我们证明在这方面,这种方法从根本上产生更好的界限比那些在现有的文献。最后,我们应用我们的结果,以提供Wasserstein界的CLT的子图计数的几何随机图的基础上$n$ i.i.d.点在欧几里得空间以及正常的近似皮尔逊统计。

英文摘要:

We propose a new functional analytic approach to Stein's method of exchangeable pairs that does not require the pair at hand to satisfy any approximate linear regression property. We make use of this theory in order to derive abstract bounds on the normal and Gamma approximation of certain functionals in the Wasserstein distance. Moreover, we illustrate the relevance of this approach by means of three instances of situations to which it can be applied: Functionals of independent random variables, finite population statistics and functionals on finite groups. In the independent case, and in particular for symmetric $U$-statistics, we demonstrate in which respect this approach yields fundamentally better bounds than those in the existing literature. Finally, we apply our results to provide Wasserstein bounds in a CLT for subgraph counts in geometric random graphs based on $n$ i.i.d. points in Euclidean space as well as to the normal approximation of Pearson's statistic.

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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