标题： 关于随机森林用于两样本检验的研究 显示英文标题

标题： On the Use of Random Forest for Two-Sample Testing

摘要： 沿分类的两样本检验思路，提出了基于随机森林分类器的检验方法。 所提出的检验易于使用，几乎不需要调节，并且适用于 $\mathbb{R}^d$上的任意分布。 此外，随机森林内置的变量重要性度量为哪些变量导致分布差异提供了潜在的见解。 针对所提出的检验方法进行了渐近功效分析。 最后，两个现实世界的应用展示了所提出方法论的实用性。 为了简化该方法的使用，提供了R语言包“hypoRF”。 显示英文摘要

摘要： Following the line of classification-based two-sample testing, tests based on the Random Forest classifier are proposed. The developed tests are easy to use, require almost no tuning, and are applicable for any distribution on $\mathbb{R}^d$. Furthermore, the built-in variable importance measure of the Random Forest gives potential insights into which variables make out the difference in distribution. An asymptotic power analysis for the proposed tests is developed. Finally, two real-world applications illustrate the usefulness of the introduced methodology. To simplify the use of the method, the R-package "hypoRF" is provided.