The Annals of Applied Statistics
- Ann. Appl. Stat.
- Volume 6, Number 3 (2012), 1162-1184.
Tree models for difference and change detection in a complex environment
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.
Ann. Appl. Stat., Volume 6, Number 3 (2012), 1162-1184.
First available in Project Euclid: 31 August 2012
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Wang, Yong; Ziedins, Ilze; Holmes, Mark; Challands, Neil. Tree models for difference and change detection in a complex environment. Ann. Appl. Stat. 6 (2012), no. 3, 1162--1184. doi:10.1214/12-AOAS548. https://projecteuclid.org/euclid.aoas/1346418578
- Supplementary material A: Data. The file arson.csv contains the Arson data that is described in Section 1 and used in the analysis throughout the paper. The meanings of the variables and the values they take on are available in Table 1.
- Supplementary material B: Software. The file difftree.R contains the R code for carrying out the analysis in the paper.