广义核双样本测试

IF 2.4 2区 数学 Q2 BIOLOGY
Biometrika Pub Date : 2023-11-14 DOI:10.1093/biomet/asad068
Hoseung Song, Hao Chen
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引用次数: 9

摘要

核二样本检验被广泛用于多变量数据的分布是否相等。然而,现有的基于将分布映射到再现内核希尔伯特空间的测试主要针对特定的替代方案,并且由于维数的诅咒,当数据的维数从中等到高时,它不能很好地工作。我们提出了一种新的测试统计量,它利用了中等和高维下的通用模式,并在广泛的替代方案中实现了对现有内核双样本测试的实质性改进。我们还提出了替代测试程序,以低计算成本保持高功率,为大型数据集提供简单的现成工具。将新方法与其他最先进的测试方法在各种设置下进行了比较,并显示出良好的性能。我们通过两个应用程序展示了新方法:使用分子形状比较麝香和非麝香,以及比较从约翰肯尼迪机场连续几个月的出租车行程。所有建议的方法都在一个R包kerTests中实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generalized kernel two-sample tests
Summary Kernel two-sample tests have been widely used for multivariate data to test equality of distributions. However, existing tests based on mapping distributions into a reproducing kernel Hilbert space mainly target specific alternatives and do not work well for some scenarios when the dimension of the data is moderate to high due to the curse of dimensionality. We propose a new test statistic that makes use of a common pattern under moderate and high dimensions and achieves substantial power improvements over existing kernel two-sample tests for a wide range of alternatives. We also propose alternative testing procedures that maintain high power with low computational cost, offering easy off-the-shelf tools for large datasets. The new approaches are compared to other state-of-the-art tests under various settings and show good performance. We showcase the new approaches through two applications: the comparison of musks and non-musks using the shape of molecules, and the comparison of taxi trips starting from John F. Kennedy airport in consecutive months. All proposed methods are implemented in an R package kerTests.
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来源期刊
Biometrika
Biometrika 生物-生物学
CiteScore
5.50
自引率
3.70%
发文量
56
审稿时长
6-12 weeks
期刊介绍: Biometrika is primarily a journal of statistics in which emphasis is placed on papers containing original theoretical contributions of direct or potential value in applications. From time to time, papers in bordering fields are also published.
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