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dc.contributor.advisorMicheas, Athanasios Christoseng
dc.contributor.authorDeWees, Todd A., 1979-eng
dc.coverage.spatialMissouri -- Kansas Cityeng
dc.date.issued2009eng
dc.date.submitted2009 Falleng
dc.descriptionThe entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.eng
dc.descriptionTitle from PDF of title page (University of Missouri--Columbia, viewed on January 28, 2011).eng
dc.descriptionThesis advisor: Dr. Athanasios C. Micheas.eng
dc.descriptionVita.eng
dc.descriptionPh. D. University of Missouri--Columbia 2009.eng
dc.description.abstract[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] We study a hierarchical Bayesian framework for finite mixtures of distributions. We first consider a Dirichlet mixture of normal components and utilize it to model spatial fields that arise as pixelated images of intensities. We demonstrate our models using results from simulated data as well as using "real-world" weather radar reflectivity fields. We propose model adequacy and verification tests to further illustrate the effectiveness of the model. We then consider and define spatio-temporal processes using a hierarchical Bayesian mixture model to help us predict the evolution of these processes based on several radar reflectivity fields observed over a short-term time period. We illustrate the methodology with simulated data and apply verification methods to demonstrate the ability of the methods to model such data. We implement these models in nowcasting the evolution of storm systems observed around the area of Kansas City, Missouri, on June 7, 2007.eng
dc.description.bibrefIncludes bibliographical references.eng
dc.identifier.oclc698776427eng
dc.identifier.urihttps://hdl.handle.net/10355/9888
dc.identifier.urihttps://doi.org/10.32469/10355/9888eng
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcommunityUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.rightsAccess is limited to the campus of the University of Missouri--Columbia.eng
dc.subject.lcshBayesian statistical decision theoryeng
dc.subject.lcshDirichlet principleeng
dc.subject.lcshRadar meteorologyeng
dc.subject.lcshReflectanceeng
dc.subject.lcshNowcasting (Meteorology)eng
dc.titleA hierarchical Bayesian mixture approach for modeling reflectivity fields with application to Nowcastingeng
dc.typeThesiseng
thesis.degree.disciplineStatistics (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelDoctoraleng
thesis.degree.namePh. D.eng


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