Accelerated group sequential sampling
Abstract We propose a novel and unified sampling scheme, called the accelerated group sequential sampling scheme, which incorporates four different types of sampling scheme: (i) the classic Anscombe–Chow–Robbins purely sequential sampling scheme; (ii) the accelerated sequential sampling scheme; (iii) the relatively new k -at-a-time group sequential sampling scheme; and (iv) the new k -at-a-time accelerated group sequential sampling scheme. The first-order and second-order properties of this unified sequential sampling scheme are fully investigated with two illustrations on minimum risk point estimation for the mean of a normal distribution and on bounded variance point estimation for the location parameter of a negative exponential distribution. We also provide extensive Monte Carlo simulation studies and real data analyses for each illustration.
Authors
- Yan Zhuang (ORCID: https://orcid.org/0000-0002-1878-6852)
- Jun Hu (ORCID: https://orcid.org/0009-0007-4786-8455)
Institutions
- Oakland University (US)
- Connecticut College (US)
Publication Details
- Journal
- Journal of Applied Probability
- Published
- 2024-12-20
- DOI
- https://doi.org/10.1017/jpr.2024.100
- Primary Topic
- Survey Sampling and Estimation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00