闫国玮, 冯龙. 分量相关的高维随机变量的最大点间距的渐近性质J. 应用概率统计, 2026, 42(2): 254-273. DOI: 10.12460/j.issn.1001-4268.aps.2026.2024064
引用本文: 闫国玮, 冯龙. 分量相关的高维随机变量的最大点间距的渐近性质J. 应用概率统计, 2026, 42(2): 254-273. DOI: 10.12460/j.issn.1001-4268.aps.2026.2024064
YAN Guowei, FENG Long. Limit Law for the Maximum Interpoint Distance of High-Dimensional Dependent VariablesJ. Chinese Journal of Applied Probability and Statistics, 2026, 42(2): 254-273.
Citation: YAN Guowei, FENG Long. Limit Law for the Maximum Interpoint Distance of High-Dimensional Dependent VariablesJ. Chinese Journal of Applied Probability and Statistics, 2026, 42(2): 254-273.

分量相关的高维随机变量的最大点间距的渐近性质

Limit Law for the Maximum Interpoint Distance of High-Dimensional Dependent Variables

  • 摘要: 本文中,我们考虑来自于 p 维总体 \boldsymbolX_1, \boldsymbolX_2, \cdots, \boldsymbolX_n 的次高斯随机变量之间的最大欧氏距离 M_n=\max _1 \leqslant i<j \leqslant n\left\|\boldsymbolX_i-\boldsymbolX_j\right\|. 当总体的维数随着样本数趋近于无穷时,我们证明了M_n^2在合适的标准化条件下渐近服从于Gumbel分布。本文中的主要证明方法依赖于Chen-Stein Poisson近似和高维情形下的高斯近似。

     

    Abstract: In this paper, we consider the limiting distribution of the maximum interpoint Euclidean distance M_n=\max _1 \leqslant i<j \leqslant n\left\|\boldsymbolX_i-\boldsymbolX_j\right\|, where \boldsymbolX_1, \boldsymbolX_2, \cdots, \boldsymbolX_n be a random sample drawn from a p dimensional population with dependent sub-Gaussian components. When the dimension tends to infinity with the sample size, we prove that M_n^2 under a suitable normalization asymptotically obeys a Gumbeltype distribution. The proofs mainly rely on the Chen-Stein Poisson approximation method and highdimensional Gaussian approximation.

     

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