Variable Window Scan Statistics for Poisson Processes

Ryan Turner () and Steven Bottone ()
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Ryan Turner: University of Cambridge
Steven Bottone: Poway

Chapter 37 in Handbook of Scan Statistics, 2024, pp 719-740 from Springer

Abstract: Abstract We present methods to do fast online anomaly detection using scan statistics. Scan statistics have long been used to detect statistically significant bursts of events. We extend the scan statistic framework to handle many practical issues that occur in application: dealing with an unknown background rate of events; allowing for slow natural changes in background frequency, the reverse problem of finding an unusual lack of events; and setting the test parameters to maximize power. We demonstrate the utility of these improvements on real and synthetic data sets with comparison to other methods.

Keywords: Upper confidence bound; Intensity estimation; Point process; Time to detection; Bisection search; Kernel smoothing; CUSUM; Snowfall; Earthquakes (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4614-8033-4_25

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DOI: 10.1007/978-1-4614-8033-4_25

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