High-dimensional k-sample comparison is a common applied problem. We construct a class of easy-to-implement nonparametric distribution-free tests based on new tools and unexplored connections with spectral graph theory. The test is shown to possess various desirable properties along with a characteristic exploratory flavor that has practical consequences. The numerical examples show that our method works surprisingly well under a broad range of realistic situations.

中文翻译：

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一种解决高维 k 样本比较问题的非参数方法

高维 k 样本比较是一个常见的应用问题。我们基于新工具和未探索的与谱图理论的联系构建了一类易于实现的非参数无分布测试。该测试被证明具有各种理想的特性以及具有实际后果的特征性探索风味。数值例子表明，我们的方法在广泛的现实情况下工作得非常好。