Geographic and network surveillance via scan statistics for critical area detection

DOI10.1214/ss/1081443229zbMath1055.62133OpenAlexW2029864877MaRDI QIDQ1764314

Charles Taillie, Ganapati P. Patil

Publication date: 24 February 2005

Published in: Statistical Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/ss/1081443229

zbMATH Keywords

hot-spot detectiongeoinformatic surveillantMonte Carlo hypothesis testingupper level setupper level set scan statistic

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12) Geostatistics (86A32)

Related Items (11)

Finite size percolation in regular trees ⋮ Cluster detection in networks using percolation ⋮ A spatial scan statistic for multiple clusters ⋮ Bayesian variable window scan statistics ⋮ Surveillance to detect emerging space-time clusters ⋮ Space‐time cluster identification in point processes ⋮ A Spatial Scan Statistic for Survival Data ⋮ Scan clustering: A false discovery approach ⋮ Flexible scan statistic test to detect disease clusters in hierarchical trees ⋮ Testing and estimation for clustered signals ⋮ Change-point problems: bibliography and review

Uses Software

• SaTScan

Cites Work

• Landscape pattern analysis for assessing ecosystem condition.
• A simulated annealing strategy for the detection of arbitrarily shaped spatial clusters
• Scan statistics and applications
• Approximation and simulation of the distributions of scan statistics for Poisson processes in higher dimensions
• Two-dimensional discrete scan statistics
• Modified Randomization Tests for Nonparametric Hypotheses
• Large-deviation approximations to the distribution of scan statistics
• A spatial scan statistic
• On the Distributions of Scan Statistics of a Two-Dimensional Poisson Process
• Prospective Time Periodic Geographical Disease Surveillance Using a Scan Statistic
• Monitoring Point Patterns for the Development of Space–Time Clusters
• Clustering of Random Points in Two Dimensions
• Scan statistics
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