Flexible scan statistic test to detect disease clusters in hierarchical trees

DOI10.1007/S00180-011-0286-9zbMath1304.65062OpenAlexW2047406185MaRDI QIDQ2512757

Marcelo Azevedo Costa, Renato M. Assunção, Marcos Oliveira Prates

Publication date: 30 January 2015

Published in: Computational Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00180-011-0286-9

zbMATH Keywords

data miningscan statisticscluster detectionexploratory analysishierarchical tree

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08)

Related Items (1)

An up-to-date review of scan statistics

Cites Work

• Unnamed Item
• A simulated annealing strategy for the detection of arbitrarily shaped spatial clusters
• Geographic and network surveillance via scan statistics for critical area detection
• A Tree-Based Scan Statistic for Database Disease Surveillance
• A spatial scan statistic
• Model Selection and the Principle of Minimum Description Length
• A Minimum Description Length-Based Image Segmentation Procedure, and Its Comparison with a Cross-Validation-Based Segmentation Procedure
• Structural Break Estimation for Nonstationary Time Series Models

This page was built for publication: Flexible scan statistic test to detect disease clusters in hierarchical trees