Permutation Inference under Dependence
EunYi Chung, University of Illinois at Urbana-Champaign
This paper studies permutation tests for dependent data. Under a weak dependence structure, we prove the asymptotic validity of block-wise permutation tests using studentization and the self- normalized test statistics, where the block size is not a function of the sample size. Monte Carlo simulation exercises confirm that both the studentized and the self- normalized block-wise permutation tests have the correct test sizes with moderate degrees of dependence.