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Tree models for difference and change detection in a complex environment. (English) Zbl 1254.62068
Summary: 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.

MSC:
62G99 Nonparametric inference
62P99 Applications of statistics
65C60 Computational problems in statistics (MSC2010)
62L99 Sequential statistical methods
Software:
R; rpart; AdaBoost.MH
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