“Quickest Change-Point Detection: The Shiryaev–Roberts Approach”

Dr. Aleksey Polunchenko, State University of New York at Binghamton

 

Date: Thursday, April 14, 2016

Time: 3:30 PM – 4:30 PM

Location: Engineering Hall Room 106B1

Sponsor: Department of Statistics

 

Abstract:

Sequential (quickest) change-point detection is the branch of statistics concerned with the design and analysis of methods for rapid but reliable anomaly detection in “live” monitored processes. The subject’s areas of application are virtually unlimited, and include quality and process control, anomaly and failure detection, surveillance and security, finance, seismology, navigation, intrusion detection, boundary tracking—to name a few. We provide a brief overview of the state-of-the-art in quickest change-point detection with particular emphasis placed on the recently proposed Generalized Shiryaev–Roberts (GSR) detection procedure (it was proposed in 2008, but the paper came out only in 2011). Notwithstanding its relatively “young age”, the GSR procedure has already been shown to have strong optimality properties not exhibited by such mainstream detection methods as the Cumulative Sum (CUSUM) “inspection scheme” and the Exponentially Weighted Moving Average (EWMA) chart.

 

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