English

Measuring Evidence against Exchangeability and Group Invariance with E-values

Statistics Theory 2026-02-11 v5 Methodology Statistics Theory

Abstract

We study e-values for quantifying evidence against exchangeability and general invariance of a random variable under a compact group. We start by characterizing such e-values, and explaining how they nest traditional group invariance tests as a special case. We show they can be easily designed for an arbitrary test statistic, and computed through Monte Carlo sampling. We prove a result that characterizes optimal e-values for group invariance against optimality targets that satisfy a mild orbit-wise decomposition property. We apply this to design expected-utility-optimal e-values for group invariance, which include both Neyman-Pearson-optimal tests and log-optimal e-values. Moreover, we generalize the notion of rank- and sign-based testing to compact groups, by using a representative inversion kernel. In addition, we characterize e-processes for group invariance for arbitrary filtrations, and provide tools to construct them. We also describe test martingales under a natural filtration, which are simpler to construct. Peeking beyond compact groups, we encounter e-values and e-processes based on ergodic theorems. These nest e-processes based on de Finetti's theorem for testing exchangeability.

Keywords

Cite

@article{arxiv.2310.01153,
  title  = {Measuring Evidence against Exchangeability and Group Invariance with E-values},
  author = {Nick W. Koning},
  journal= {arXiv preprint arXiv:2310.01153},
  year   = {2026}
}
R2 v1 2026-06-28T12:38:13.855Z