DETECTING A CHANGE OF A NORMAL-MEAN BY DYNAMIC SAMPLING WITH A PROBABILITY BOUND ON A FALSE ALARM

• 成果类型: Article
• 署名作者: ASSAF, D; POLLAK, M; RITOV, Y; YAKIR, B
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/aos/1176349255
• 发表日期: 1993
• 页码: 1155-1165
• 关键词: brownian-motion; drift

摘要

We show that when dynamic sampling is feasible, there exist surveillance schemes for which the probability of a false alarm is bounded and which have a bounded expected delay when detecting a (true) change. In the case of detecting a change of a normal mean, we probe optimality and suggest procedures. These procedures compare favorably to those having a fixed sampling rate which have been developed for an expectation constraint on the average run length until a false alarm.