Improving the fully sequential sampling scheme of Anscombe-Chow-Robbins
成果类型：
Article
署名作者：
Liu, W
署名单位：
University of Southampton
刊物名称：
ANNALS OF STATISTICS
ISSN/ISSBN：
0090-5364
DOI：
10.1214/aos/1069362392
发表日期：
1997
页码：
2164-2171
关键词：
摘要：
A new sequential sampling scheme is proposed in which, after an initial batch sample, sampling is continued in batches of data-dependent sizes (at most k such batches), and then one-at-a-time with a data-dependent stopping rule. This new scheme requires about the same sample size as the fully sequential Anscombe-Chow-Robbins (ACR) sampling scheme but substantially fewer sampling operations. The problem of constructing fixed-width confidence intervals for the mean of a normal population with unknown variance is used as an illustration.