Sequential change detection revisited

• 成果类型: Article
• 署名作者: Moustakides, George V.
• 署名单位: University of Patras
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/009053607000000938
• 发表日期: 2008
• 页码: 787-807
• 关键词: poisson disorder problem; cusum procedure; exponential penalty; continuous-time; optimality; delay

摘要

In sequential change detection, existing performance measures differ significantly in the way they treat the time of change. By modeling this quantity as a random time, we introduce a general framework capable of capturing and better understanding most well-known criteria and also propose new ones. For a specific new criterion that constitutes an extension to Lorden's performance measure, we offer the optimum structure for detecting a change in the constant drift of a Brownian motion and a formula for the corresponding optimum performance.