Efficiency of nonparametric e-tests
Not on the map. Why?
Abstract (arXiv)
The notion of an e-value has been recently proposed as a possible alternative to critical regions and p-values in statistical hypothesis testing. In this paper we consider testing the nonparametric hypothesis of symmetry, introduce analogues for e-values of three popular nonparametric tests, define an analogue for e-values of Pitman's asymptotic relative efficiency, and apply it to the three nonparametric tests. We discuss limitations of our simple definition of asymptotic relative efficiency and list directions of further research.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Aug 2022.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2023: 1; 2024: 2.
3 papers.
- 2024Peeking with PEAK: Sequential, Nonparametric Composite Hypothesis Tests for Means of Multiple Data Streamscited by 9
- 2024Reward Maximization for Pure Exploration: Minimax Optimal Good Arm Identification for Nonparametric Multi-Armed Banditscited by 5
- 2023Anytime-valid t-tests and confidence sequences for Gaussian means with unknown variancecited by 2
- 2024Reward Maximization for Pure Exploration: Minimax Optimal Good Arm Identification for Nonparametric Multi-Armed Bandits21 Oct 2024
- 2024Peeking with PEAK: Sequential, Nonparametric Composite Hypothesis Tests for Means of Multiple Data Streams9 Feb 2024
- 2023Anytime-valid t-tests and confidence sequences for Gaussian means with unknown variance5 Oct 2023