利用点间距离差异进行新的双样本检验

IF 0.7 4区 数学 Q3 STATISTICS & PROBABILITY
Stat Pub Date : 2024-07-22 DOI:10.1002/sta4.712
Dong Xu
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引用次数: 0

摘要

本文提出了一种新颖的多元样本空间双样本检验方法。该检验统计量计算平均点间距离绝对差的平均值。我们利用置换程序来确定检验的临界值。通过综合模拟研究,我们比较了我们提出的检验与 K 最近邻检验和能量检验的性能。结果表明,我们提出的检验方法比其他两种检验方法更具优势,尤其是在高维样本空间中。在 UCR 时间序列数据集上的应用进一步验证了这一优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New two‐sample test utilizing interpoint distance discrepancy
In this paper, we propose a novel two‐sample test for multivariate sample space. The test statistic calculates the mean of absolute difference of average interpoint distance. We utilize a permutation procedure to establish the critical value for the test. Through comprehensive simulation studies, we compare the performance of our proposed test with that of the K‐nearest neighbour test and the energy test. The results demonstrate that our proposed test exhibits advantages over the other two tests, particularly in high‐dimensional sample spaces. This superiority is further validated by its application to UCR time series datasets.
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来源期刊
Stat
Stat Decision Sciences-Statistics, Probability and Uncertainty
CiteScore
1.10
自引率
0.00%
发文量
85
期刊介绍: Stat is an innovative electronic journal for the rapid publication of novel and topical research results, publishing compact articles of the highest quality in all areas of statistical endeavour. Its purpose is to provide a means of rapid sharing of important new theoretical, methodological and applied research. Stat is a joint venture between the International Statistical Institute and Wiley-Blackwell. Stat is characterised by: • Speed - a high-quality review process that aims to reach a decision within 20 days of submission. • Concision - a maximum article length of 10 pages of text, not including references. • Supporting materials - inclusion of electronic supporting materials including graphs, video, software, data and images. • Scope - addresses all areas of statistics and interdisciplinary areas. Stat is a scientific journal for the international community of statisticians and researchers and practitioners in allied quantitative disciplines.
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