In the regime of two-sample comparison, tests based on a graph constructed on observations by utilizing similarity information among them is gaining attention due to their flexibility and good performances for high-dimensional/non-Euclidean data. However, when there are repeated observations, these graph-based tests could be problematic as they are versatile to the choice of the similarity graph. We propose extended graph-based test statistics to resolve this problem. The analytic p-value approximations to these extended graph-based tests are derived to facilitate the application of these tests to large datasets. The new tests are illustrated in the analysis of a phone-call network dataset. All tests are implemented in an R package gTests.

中文翻译：

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重复观察数据的基于图的双样本检验

在两样本比较的情况下，基于通过利用它们之间的相似性信息构建的观察图的测试由于其灵活性和对高维/非欧几里德数据的良好性能而受到关注。然而，当有重复的观察时，这些基于图的测试可能会出现问题，因为它们对于相似图的选择是通用的。我们提出扩展的基于图的测试统计来解决这个问题。导出这些扩展的基于图的测试的分析 p 值近似值，以促进将这些测试应用于大型数据集。新测试在电话网络数据集的分析中得到了说明。所有测试都在 R 包 gTests 中实现。