Classification Analysis for Environmental Monitoring: Combining Information across Multiple Studies

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dc.contributor.authorZhang, Huizien
dc.contributor.committeechairSmith, Eric P.en
dc.contributor.committeememberYe, Keyingen
dc.contributor.committeememberBoone, Edwarden
dc.contributor.committeememberPrins, Samantha C. Batesen
dc.contributor.departmentStatisticsen
dc.date.accessioned2014-03-14T20:15:25Zen
dc.date.adate2006-09-29en
dc.date.available2014-03-14T20:15:25Zen
dc.date.issued2006-08-14en
dc.date.rdate2006-09-29en
dc.date.sdate2006-08-19en
dc.description.abstractEnvironmental studies often employ data collected over large spatial regions. Although it is convenient, the conventional single model approach may fail to accurately describe the relationships between variables. Two alternative modeling approaches are available: one applies separate models for different regions; the other applies hierarchical models. The separate modeling approach has two major difficulties: first, we often do not know the underlying clustering structure of the entire data; second, it usually ignores possible dependence among clusters. To deal with the first problem, we propose a model-based clustering method to partition the entire data into subgroups according to the empirical relationships between the response and the predictors. To deal with the second, we propose Bayesian hierarchical models. We illustrate the use of the Bayesian hierarchical model under two situations. First, we apply the hierarchical model based on the empirical clustering structure. Second, we integrate the model-based clustering result to help determine the clustering structure used in the hierarchical model. The nature of the problem is classification since the response is categorical rather than continuous and logistic regression models are used to model the relationship between variables.en
dc.description.degreePh. D.en
dc.identifier.otheretd-08192006-115350en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-08192006-115350/en
dc.identifier.urihttp://hdl.handle.net/10919/28721en
dc.publisherVirginia Techen
dc.relation.haspartdissertation.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectEnvironmental studiesen
dc.subjectClusteringen
dc.subjectHierarchical Modelen
dc.subjectClassificationen
dc.titleClassification Analysis for Environmental Monitoring: Combining Information across Multiple Studiesen
dc.typeDissertationen
thesis.degree.disciplineStatisticsen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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