Sequential (Quickest) Change Detection: Classical Results and New Directions

2021/04/09 by Liyan Xie, Shaofeng Zou, Xie, Liyan +5 · 9 citations
Decision Sciences · Mathematics · Medicine · #Advanced Statistical Process Monitoring #Data-Driven Disease Surveillance #Statistical Methods and Inference #math.ST #stat.TH

paper · pdf · doi:10.48550/arxiv.2104.04186

arxiv created 2021/04/09 · arxiv updated 2021/04/12

Abstract

Online detection of changes in stochastic systems, referred to as sequential change detection or quickest change detection, is an important research topic in statistics, signal processing, and information theory, and has a wide range of applications. This survey starts with the basics of sequential change detection, and then moves on to generalizations and extensions of sequential change detection theory and methods. We also discuss some new dimensions that emerge at the intersection of sequential change detection with other areas, along with a selection of modern applications and remarks on open questions.

Citations

• On the distribution of the largest eigenvalue in principal components analysis
• CONTINUOUS INSPECTION SCHEMES
• On optimality of the Shiryaev–Roberts procedure for detecting a change in distribution

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