Detecting local regions of change in high-dimensional criminal or terrorist point processes

DOI10.1016/j.csda.2006.07.002zbMath1161.62463OpenAlexW2073163008WikidataQ57445100 ScholiaQ57445100MaRDI QIDQ1019904

Donald E. Brown, Michael D. Porter

Publication date: 29 May 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2006.07.002

zbMATH Keywords

change detectionrandom labelingmarked spatial point processPRIMspatial scan statistic

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Monte Carlo methods (65C05) Applications of statistics (62P99)

Related Items

Space-time border analysis to evaluate and detect clusters

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Power comparisons for disease clustering tests
• Scan statistics and applications
• Multiple Window Discrete Scan Statistics
• Large-deviation approximations to the distribution of scan statistics
• A spatial scan statistic
• A Spatial Scan Statistic for Stochastic Scan Partitions
• Monitoring Point Patterns for the Development of Space–Time Clusters
• An Introduction to the Theory of Point Processes
• Importance sampling for spatial scan analysis: computing scan statistic \(p-\)values for marked point processes.