2 papers
stat.CO2026
More Permutations Do Not Always Increase Power: Non-monotonicity in Monte Carlo Permutation Tests
Suman Cha, Seongchan Lee, Antonin Schrab +1
Monte Carlo permutation tests are a cornerstone of valid, model-free statistical inference. A widely held practical intuition is that increasing the number of sampled permutations…
stat.ML2026
Regularized -Divergence Kernel Tests
Mónica Ribero, Antonin Schrab, Arthur Gretton
We propose a framework to construct practical kernel-based two-sample tests from the family of -divergences. The test statistic is computed from the witness function of a regula…