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GLS-SOD: A Generalized Local Statistical Approach for Spatial Outlier Detection

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dc.contributor.authorChen, Fengen
dc.contributor.authorLu, Chang-Tienen
dc.contributor.authorBoedihardjo, Arnold P.en
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2013-06-19T14:36:41Zen
dc.date.available2013-06-19T14:36:41Zen
dc.date.issued2010-03-01en
dc.description.abstractLocal based approach is a major category of methods for spatial outlier detection (SOD). Currently, there is a lack of systematic analysis on the statistical properties of this framework. For example, most methods assume identical and independent normal distributions (i.i.d. normal) for the calculated local differences, but no justifications for this critical assumption have been presented. The methods’ detection performance on geostatistic data with linear or nonlinear trend is also not well studied. In addition, there is a lack of theoretical connections and empirical comparisons between local and global based SOD approaches. This paper discusses all these fundamental issues under the proposed generalized local statistical (GLS) framework. Furthermore, robust estimation and outlier detection methods are designed for the new GLS model. Extensive simulations demonstrated that the SOD method based on the GLS model significantly outperformed all existing approaches when the spatial data exhibits a linear or nonlinear trend.en
dc.format.mimetypeapplication/pdfen
dc.identifierhttp://eprints.cs.vt.edu/archive/00001110/en
dc.identifier.sourceurlhttp://eprints.cs.vt.edu/archive/00001110/01/GLS.PDFen
dc.identifier.trnumberTR-10-03en
dc.identifier.urihttp://hdl.handle.net/10919/19381en
dc.language.isoenen
dc.publisherDepartment of Computer Science, Virginia Polytechnic Institute & State Universityen
dc.relation.ispartofComputer Science Technical Reportsen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectNumerical analysisen
dc.titleGLS-SOD: A Generalized Local Statistical Approach for Spatial Outlier Detectionen
dc.typeTechnical reporten
dc.type.dcmitypeTexten

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