Dissertation
E-values for anytime-valid inference with exponential families
Traditional hypothesis testing requires researchers to set a fixed sample size in advance. After collecting data, the test determines whether to reject the null hypothesis.
- Author
- Y. Hao
- Date
- 18 February 2025
- Links
- Thesis in Leiden Repository
In contrast, modern approaches like anytime-valid tests (e.g., methods based on e-values and e-processes) provide greater flexibility. These methods allow researchers to assess evidence continuously as data is gathered, eliminating the need for a pre-determined sample size. E-values, in particular, do not require predefined stopping rules for the experiment. This dissertation focuses on the application of e-values and e-processes within exponential families.