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Multiple Window Discrete Scan Statistics

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In this article, multiple scan statistics of variable window sizes are derived for independent and identically distributed 0-1 Bernoulli trials. Both one and two dimensional, as well as, conditional and unconditional cases are treated. The advantage in using multiple scan statistics, as opposed to single fixed window scan statistics, is that they are more sensitive in detecting a change in the underlying distribution of the observed data. We show how to derive simple approximations for the significance level of these testing procedures and present numerical results to evaluate their performance.
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Keywords: Combining test statistics; one-dimensional scan statistics; p-values; two-dimensional scan statistics; variable windows

Document Type: Research Article

Affiliations: University of Connecticut, Connecticut, USA

Publication date: October 1, 2004

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