Rollout designs for lump-sum data
This work studies rollout design problems with a focus of suitable choices of rollout rate under the standard Type I and Type II error probabilities control framework. The main challenge of rollout design is that data is often observed in a lump-sum manner from a spatio-temporal point of view: (1) temporally, only the sum of data in a given sliding time window can be observed; (2) spatially, there are two subgroups for the data at each time step: control and treatment, but one can only observe the total values instead of individual values from each subgroup. We develop rollout tests of lump-sum data under both fixed-sample-size and sequential settings, subject to the constraints on Type I and Type II error probabilities. Numerical studies are conducted to validate our theoretical results.
Authors
- Yajun Mei (ORCID: https://orcid.org/0000-0002-1015-990X)
- Hongzhen Tian (ORCID: https://orcid.org/0000-0002-5779-8856)
- Anup Kumar Sarkar (ORCID: https://orcid.org/0000-0002-6418-4895)
- Qinkai Xu
Institutions
- Microsoft (United States) (US)
- Microsoft Research (United Kingdom) (GB)
- New York University (US)
Publication Details
- Journal
- Journal of Applied Statistics
- Published
- 2024-12-13
- DOI
- https://doi.org/10.1080/02664763.2024.2440031
- Primary Topic
- Advanced Statistical Process Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation