Quickest Detection with Discretely Controlled Observations

Abstract

We study a continuous time Bayesian quickest detection problem in which observation times are a scarce resource. The agent, limited to making a finite number of discrete observations, must adaptively decide his observation strategy to minimize detection delay and the probability of false alarm. Under two different models of observation rights, we establish the existence of optimal strategies, and formulate an algorithmic approach to the problem via jump operators. We describe algorithms for these problems, and illustrate them with some numerical results. As the number of observation rights tends to infinity, we also show convergence to the classical continuous observation problem of Shiryaev.

Final version. To appear in Sequential Analysis. Keywords: Bayesian changepoint detection; Continuous time; Finitely many sampling rights. 52 pages

References in corpus (2)

• Adaptive Poisson disorder problem
• Data-Efficient Quickest Change Detection in Minimax Settings

Cited by in corpus (3)

• Yau-Tian-Donaldson correspondence for K-semistable Fano manifolds
• A quickest detection problem with an observation cost
• Bayesian Quickest Change Point Detection with Sampling Right Constraints