Asymptotic Validity and Finite-Sample Properties of Approximate Randomization Tests

arXiv:1908.04218v3 Announce Type: replace-cross
Abstract: Randomization tests rely on simple data transformations and possess an appealing robustness property. In addition to being finite-sample valid if the data distribution is invariant under the transformation, these tests can be asymptotically valid under a suitable studentization of the test statistic, even if the invariance does not hold. However, practical implementation often encounters noisy data, resulting in approximate randomization tests that may not be as robust. In this paper, our key theoretical contribution is …

abstract arxiv data distribution property randomization robustness sample simple stat.me stat.ml test tests transformation type