Detecting changes in a Poisson process monitored at uneven time intervals where the arrival rates are unknown. Issue 2 (3rd April 2018)

• Record Type: Journal Article
• Authors: Brown, Marlo
• Is Part Of: Sequential analysis. Volume 37:Issue 2(2018)
• Page Start: 235
• Page End: 245
• Publication Date: 2018-04-03
• Subjects: Bayesian stopping rules -- change-point detection -- dynamic programming -- Poisson processes -- risk -- unknown arrivals; 62L15 -- 60G40; Sequential analysis -- Periodicals; 519.54
• DOI: 10.1080/07474946.2018.1466538
• Languages: English
• ISSNs: 0747-4946

Abstract

Abstract: We look at a Poisson process where the arrival rate changes at some unknown time point. We monitor this process only at certain time points. At each time point, we count the number of arrivals that happened in that time interval. We assume that the times at which the process is observed is fixed but uneven. In previous papers, we assumed that the arrival rates both before after the change are known. In this article, we assume that the arrival rates both before the change and after the change are unknown. We only know that when the change happens, this results in an increasing arrival rate.