NDLI: Detecting high incidence by using variable scan radius

Content Provider	IEEE Xplore Digital Library
Author	Chen-ju Lin Yi-chun Shu
Copyright Year	2013
Description	Author affiliation: Dept. of Ind. Eng. & Manage., Yuan Ze Univ., Chungli, Taiwan (Chen-ju Lin; Yi-chun Shu)
Abstract	This research aims at detecting spatiotemporal clustering with increased mean. Scan statistics are popular methods for spatiotemporal surveillance. Several likelihood-ratio (LR) and exponentially weighted moving average (EWMA) based scan statistics have been studied for the scenarios with known or unknown size of shifted coverage. However, the existing EWMA-based methods applying fixed radii may not be efficient to detect the cluster with unknown shifted coverage. This paper proposed an EWMA-based scan statistic with variable scan radii to detect clustering instead. The proposed statistic weights the observations by distance in each circular scan window and uses the EWMA technique across the temporal axis. Comparing to the LR-based scan statistic with variable scan radii, the proposed method can be more sensitive when clusters occur at the early stage. The proposed method would have advantage in solving practical problems with unknown size of shift coverage.
Starting Page	275
Ending Page	279
File Size	1362751
Page Count	5
File Format	PDF
ISBN	9781479909865
DOI	10.1109/IEEM.2013.6962417
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-10
Publisher Place	Thailand
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Maximum likelihood estimation Accuracy Shape Surveillance clustering Spatiotemporal phenomena Spatiotemporal surveillance Diseases scan statistic
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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