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September 2012 Tree models for difference and change detection in a complex environment
Yong Wang, Ilze Ziedins, Mark Holmes, Neil Challands
Ann. Appl. Stat. 6(3): 1162-1184 (September 2012). DOI: 10.1214/12-AOAS548

Abstract

A new family of tree models is proposed, which we call “differential trees.” A differential tree model is constructed from multiple data sets and aims to detect distributional differences between them. The new methodology differs from the existing difference and change detection techniques in its nonparametric nature, model construction from multiple data sets, and applicability to high-dimensional data. Through a detailed study of an arson case in New Zealand, where an individual is known to have been laying vegetation fires within a certain time period, we illustrate how these models can help detect changes in the frequencies of event occurrences and uncover unusual clusters of events in a complex environment.

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Yong Wang. Ilze Ziedins. Mark Holmes. Neil Challands. "Tree models for difference and change detection in a complex environment." Ann. Appl. Stat. 6 (3) 1162 - 1184, September 2012. https://doi.org/10.1214/12-AOAS548

Information

Published: September 2012
First available in Project Euclid: 31 August 2012

zbMATH: 1254.62068
MathSciNet: MR3012525
Digital Object Identifier: 10.1214/12-AOAS548

Rights: Copyright © 2012 Institute of Mathematical Statistics

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Vol.6 • No. 3 • September 2012
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