Campus Units
Statistics, Center for Survey Statistics and Methodology (CSSM)
Document Type
Article
Publication Version
Accepted Manuscript
Publication Date
2013
Journal or Book Title
Statistics and Its Interface
Volume
6
Issue
1
First Page
65
Last Page
77
DOI
10.4310/SII.2013.v6.n1.a7
Abstract
A novel multi-resolution cluster detection (MCD) method is proposed to identify irregularly shaped clusters in space. Multi-scale test statistic on a single cell is derived based on likelihood ratio statistic for Bernoulli sequence, Poisson sequence and Normal sequence. A neighborhood variability measure is defined to select the optimal test threshold. The MCD method is compared with single scale testing methods controlling for false discovery rate and the spatial scan statistics using simulation and f-MRI data. The MCD method is shown to be more effective for discovering irregularly shaped clusters, and the implementation of this method does not require heavy computation, making it suitable for cluster detection for large spatial data.
Copyright Owner
International Press
Copyright Date
2013
Language
en
File Format
application/pdf
Recommended Citation
Zhang, Lingsong and Zhu, Zhengyuan, "Spatial multiresolution cluster detection method" (2013). Statistics Publications. 300.
https://lib.dr.iastate.edu/stat_las_pubs/300
Comments
This is a manuscript of an article published as Zhang, Lingsong, and Zhengyuan Zhu. "Spatial multiresolution cluster detection method." Statistics and Its Interface 6, no. 1 (2013): 65-77. DOI: 10.4310/SII.2013.v6.n1.a7. Posted with permission.