A new adaptive procedure for multiple window scan statistics

Tung-Lung Wu and Joseph Glaz

Computational Statistics & Data Analysis, 2015, vol. 82, issue C, 164-172

Abstract: Scan statistics have been widely applied to test for unusual cluster of events in many scientific areas. It has been of practical interest on how to select the window size of a scan statistic. An adaptive procedure for multiple window scan statistics is proposed and the distributions are studied for independent identically distributed Bernoulli trials and uniform observations on (0, 1) in one-dimensional case. The idea of the procedure is to select the window sizes sequentially. An initial window size is chosen and the subsequent window sizes are then determined, depending on the value of the current scan statistic at each stage. The power of scan statistics based on the adaptive procedure is compared with power of standard scan statistics. Numerical results and applications for disease clusters detection are given to illustrate our procedure.

Keywords: Adaptive procedure; Clusters; Multiple window scan statistics; Sequential; Window size; Two-dimensional (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S016794731400262X
Full text for ScienceDirect subscribers only.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:82:y:2015:i:c:p:164-172

DOI: 10.1016/j.csda.2014.09.002

Access Statistics for this article

Computational Statistics & Data Analysis is currently edited by S.P. Azen

More articles in Computational Statistics & Data Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().