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| Type | Working Paper |
| Scope | Discipline-based scholarship |
| Title | On the Use of Random Forest for Two-Sample Testing |
| Organization Unit | |
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| Institution | Cornell University |
| Series Name | ArXiv.org |
| Number | 190306287 |
| ISSN | 2331-8422 |
| Date | 2019 |
| Abstract Text | We follow the line of using classifiers for two-sample testing and propose several tests based on the Random Forest classifier. The developed tests are easy to use, require no tuning and are applicable for any distribution on Rp, even in high-dimensions. We provide a comprehensive treatment for the use of classification for two-sample testing, derive the distribution of our tests under the Null and provide a power analysis, both in theory and with simulations. To simplify the use of the method, we also provide the R-package "hypoRF". |
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| Digital Object Identifier | 10.48550/arXiv.1903.06287 |
| Other Identification Number | merlin-id:17699 |
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