Read, S., Bath, P.A., Willett, P. and Maheswaran, R. (2010) A Power-Enhanced Algorithm for Spatial Anomaly Detection in Binary Labelled Point Data Using the Spatial Scan Statistic [postprint]. In: 14th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, Sept 8th-10th, Cardiff UK. 14th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, Sept 8th-10th, 2010, Cardiff, UK. Lecture Notes in Artificial Intelligence, II (6277). Springer Verlag , Berlin , pp. 163-172.
This paper presents a novel modification to an existing algorithm for spatial anomaly detection in binary labeled point data sets, using the Bernoulli version of the Spatial Scan Statistic. We identify a potential ambiguity in p-values produced by Monte Carlo testing, which (by the selection of the most conservative p-value) can lead to sub-optimal power. When such ambiguity occurs, the modification uses a very inexpensive secondary test to suggest a less conservative p-value. Using benchmark tests, we show that this appears to restore power to the expected level, whilst having similarly retest variance to the original. The modification also appears to produce a small but significant improvement in overall detection performance when multiple anomalies are present.
|Copyright, Publisher and Additional Information:||This paper will appear in 'Lecture Notes in Artificial Intelligence'. Uploaded in accordance with the publisher's self-archiving policy. The published paper will be available from www.springerlink.com|
|Keywords:||spatial scan statistic, bernoulli, power, benchmark testing, multiple clusters|
|Institution:||The University of Sheffield|
|Academic Units:||The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Health and Related Research (Sheffield) > Section of Public Health (Sheffield)
The University of Sheffield > Faculty of Social Sciences (Sheffield) > Information School (Sheffield)
|Depositing User:||Dr Simon Read|
|Date Deposited:||21 Jul 2010 10:37|
|Last Modified:||13 May 2014 09:40|