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dc.contributor.advisorSarkar, S. K. (Sanat K.)
dc.creatorClements, Nicolle
dc.date.accessioned2020-11-03T16:23:37Z
dc.date.available2020-11-03T16:23:37Z
dc.date.issued2013
dc.identifier.other890207794
dc.identifier.urihttp://hdl.handle.net/20.500.12613/2701
dc.description.abstractThis dissertation is focused on multiple testing procedures to be used in data that are naturally grouped or possess a spatial structure. We propose `Two-Stage' procedure to control the False Discovery Rate (FDR) in situations where one-sided hypothesis testing is appropriate, such as astronomical source detection. Similarly, we propose a `Three-Stage' procedure to control the mixed directional False Discovery Rate (mdFDR) in situations where two-sided hypothesis testing is appropriate, such as vegetation monitoring in remote sensing NDVI data. The Two and Three-Stage procedures have provable FDR/mdFDR control under certain dependence situations. We also present the Adaptive versions which are examined under simulation studies. The `Stages' refer to testing hypotheses both group-wise and individually, which is motivated by the belief that the dependencies among the p-values associated with the spatially oriented hypotheses occur more locally than globally. Thus, these `Staged' procedures test hypotheses in groups that incorporate the local, unknown dependencies of neighboring p-values. If a group is found significant, further investigation is done to the individual p-values within that group. For the vegetation monitoring data, we extend the investigation by providing some spatio-temporal models and forecasts to some regions where significant change was detected through the multiple testing procedure.
dc.format.extent98 pages
dc.language.isoeng
dc.publisherTemple University. Libraries
dc.relation.ispartofTheses and Dissertations
dc.rightsIN COPYRIGHT- This Rights Statement can be used for an Item that is in copyright. Using this statement implies that the organization making this Item available has determined that the Item is in copyright and either is the rights-holder, has obtained permission from the rights-holder(s) to make their Work(s) available, or makes the Item available under an exception or limitation to copyright (including Fair Use) that entitles it to make the Item available.
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectStatistics
dc.subjectAstronomy
dc.subjectFalse Discovery Rate
dc.subjectFdr
dc.subjectMdfdr
dc.subjectMultiple Testing
dc.subjectNdvi
dc.titleMultiple Testing in Grouped Dependent Data
dc.typeText
dc.type.genreThesis/Dissertation
dc.contributor.committeememberZhao, Zhigen
dc.contributor.committeememberWei, William W. S.
dc.contributor.committeememberHeiberger, Richard M.
dc.contributor.committeememberObradovic, Zoran
dc.description.departmentStatistics
dc.relation.doihttp://dx.doi.org/10.34944/dspace/2683
dc.ada.noteFor Americans with Disabilities Act (ADA) accommodation, including help with reading this content, please contact scholarshare@temple.edu
dc.description.degreePh.D.
refterms.dateFOA2020-11-03T16:23:37Z


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