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.

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.

Copyright Owner

International Press

Language

en

File Format

application/pdf

Published Version

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