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An Adaptive Minimum Spanning Tree Test for Detecting Irregularly-Shaped Spatial Clusters
Ruoyu Zhou1; Lianjie Shu1; Yan Su2
2015
Source PublicationComputational Statistics & Data Analysis
ISSN0167-9473
Volume89Pages:134-146
Abstract

The clustering methodologies based on minimum spanning tree (MST) have been widely discussed due to their simplicity and efficiency in signaling irregular clusters. However, most of the MST-based clustering methods estimate the most likely cluster based on the maximum likelihood ratio from the resulting subtrees after the removal of edges of the MST. They can only estimate one cluster even if there are multiple clusters actually present over the study region. To overcome this limitation, we propose an adaptive MST (AMST) method to detect irregularly-shapedclusters.The basic idea is to first determine the best number of partition over the study region using a validity index and then to determine the significance of the candidate clusters. The comparison results with both the static and dynamic MST methods favor the proposed method.

KeywordMinimum Spanning Tree Spatial Cluster Detection Arbitrary Shape Validity Index
DOI10.1016/j.csda.2015.03.008
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Mathematics
WOS SubjectComputer Science, Interdisciplinary Applications ; Statistics & Probability
WOS IDWOS:000357348000011
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Citation statistics
Cited Times [WOS]:4   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF ACCOUNTING AND INFORMATION MANAGEMENT
Faculty of Science and Technology
DEPARTMENT OF ELECTROMECHANICAL ENGINEERING
Corresponding AuthorLianjie Shu
Affiliation1.Faculty of Business, University of Macau, Macau
2.Department of Electromechanical Engineering, University of Macau, Macau
First Author AffilicationUniversity of Macau
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Ruoyu Zhou,Lianjie Shu,Yan Su. An Adaptive Minimum Spanning Tree Test for Detecting Irregularly-Shaped Spatial Clusters[J]. Computational Statistics & Data Analysis,2015,89:134-146.
APA Ruoyu Zhou,Lianjie Shu,&Yan Su.(2015).An Adaptive Minimum Spanning Tree Test for Detecting Irregularly-Shaped Spatial Clusters.Computational Statistics & Data Analysis,89,134-146.
MLA Ruoyu Zhou,et al."An Adaptive Minimum Spanning Tree Test for Detecting Irregularly-Shaped Spatial Clusters".Computational Statistics & Data Analysis 89(2015):134-146.
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