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新的统计方法改进了高维U统计量的分析

研究人员开发了一种分析高维U统计量的新方法。U统计量是用于计量经济学等各个领域的复杂统计量。该方法提供了一个显式阶次的大偏差界限,详细说明了U统计量与其Hájek投影之间的最大偏差。这一进展包括新的矩不等式,并为这些统计量带来了改进的集中度和高斯近似结果。这些发现对于建立非参数回归估计量(如随机森林中使用的估计量)的基于重采样的置信区间的一致性具有实际应用价值。 AI

影响 为可能应用于机器学习领域的高级统计分析提供了理论基础。

排序理由 详细介绍了一种新颖的统计方法及其理论性质的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv stat.ML 阅读 →

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新的统计方法改进了高维U统计量的分析

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详细介绍了一种新颖的统计方法及其理论性质的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv stat.ML TIER_1 English(EN) · David M. Ritzwoller, Vasilis Syrgkanis ·

    高维$U$-统计量的顺序显式线性化

    arXiv:2405.07860v4 Announce Type: replace-cross Abstract: We give an order-explicit large deviation bound for the difference between a high-dimensional $U$-statistic and its H\'{a}jek projection. In particular, we show that any $U$-statistic of order $b$ on $n$ observations, with…