Evaluation of hotspot cluster detection using spatial scan statistic based on exact counting

DOI10.1007/s42081-018-0030-6zbMath1430.62230OpenAlexW2913425001WikidataQ127866353 ScholiaQ127866353MaRDI QIDQ2329882

Masahiro Mizuta, Shin-ichi Minato, Jun Kawahara, Koji Kurihara, Fumio Ishioka

Publication date: 18 October 2019

Published in: Japanese Journal of Statistics and Data Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s42081-018-0030-6

zbMATH Keywords

echelon analysisspatial cluster detectionspatial scan statisticzero-suppressed binary decision diagram

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (4)

Detection of space-time clusters using a topological hierarchy for geospatial data on COVID-19 in Japan ⋮ Spatial and temporal clustering based on the echelon scan technique and software analysis ⋮ An up-to-date review of scan statistics ⋮ Special feature: Computational statistics and machine learning

Uses Software

• SaTScan

Cites Work

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• A simulated annealing strategy for the detection of arbitrarily shaped spatial clusters
• Generating All Patterns of Graph Partitions Within a Disparity Bound
• Spatial Modeling of Regional Variables
• Modified Randomization Tests for Nonparametric Hypotheses
• A spatial scan statistic
• Weighted Normal Spatial Scan Statistic for Heterogeneous Population Data
• A Spatial Scan Statistic for Survival Data

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