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On the Use of Random Forest for Two-Sample Testing

Hediger, Simon; Michel, Loris; Näf, Jeffrey (2019). On the Use of Random Forest for Two-Sample Testing. ArXiv.org 190306287, Cornell University.

Abstract

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".

Additional indexing

Item Type:Working Paper
Communities & Collections:03 Faculty of Economics > Department of Finance
Dewey Decimal Classification:330 Economics
Scope:Discipline-based scholarship (basic research)
Language:English
Date:2019
Deposited On:03 Nov 2021 10:18
Last Modified:27 May 2024 15:24
Series Name:ArXiv.org
ISSN:2331-8422
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.48550/arXiv.1903.06287
Related URLs:https://www.zora.uzh.ch/id/eprint/214194/
Other Identification Number:merlin-id:17699
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  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)

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