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 \emph{any} distribution on
Link to the pre-print: https://arxiv.org/abs/1903.06287
- Install the Python module found on https://github.com/wittawatj/interpretable-test from Wittawat Jitkrittum via the command:
pip install git+https://github.com/wittawatj/interpretable-test
Once installed, you should be able toimport freqopttest
. - Install the R-package
hypoRF
found in\hypoRF_Code\hypoRF
via `the R commandinstall.packages("./hypoRF/", repos = NULL, type = "source")
. - Make sure you have installed the R-packages
ranger
,mvtnorm
,reticulate
,MASS
andparSim
(only necessary if you are interested in parallel computing). - Launch the desired simulation R-file locally in the folder \hypoRF_Code\Replicate_Simulations. If you want to save or plot any result, use the outcommented code at the end of each script.