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dc.contributor.authorVaughan, Amy
dc.date.accessioned2014-03-04T18:25:47Z
dc.date.available2014-03-04T18:25:47Z
dc.date.issued2009-12
dc.identifier.othervaughan_amy_g_200912_phd
dc.identifier.urihttp://purl.galileo.usg.edu/uga_etd/vaughan_amy_g_200912_phd
dc.identifier.urihttp://hdl.handle.net/10724/26177
dc.description.abstractSiZer (SIgnificant ZERo crossing of the derivatives) is a scale-space visualization tool for statistical inferences. In this paper we introduce a graphical device, which is based on SiZer, for the test of the equality of the mean of two time series. The estimation of the quantile in a confidence interval is theoretically justified by advanced distribution theory. The extension of the proposed method to the comparison of more than two time series is also done using residual analysis. A broad numerical study is conducted to demonstrate the sample performance of the proposed tool. In addition, asymptotic properties of SiZer for the comparison of two time series are investigated.
dc.languageeng
dc.publisheruga
dc.rightspublic
dc.subjectComparison of multiple time series
dc.subjectLocal linear smoothing
dc.subjectMultiple testing adjustment
dc.subjectSiZer
dc.subjectWeak convergence
dc.titleStatistical inferences and visualization based on a scale-space approach
dc.typeDissertation
dc.description.degreePhD
dc.description.departmentStatistics
dc.description.majorStatistics
dc.description.advisorCheolwoo Park
dc.description.committeeCheolwoo Park
dc.description.committeeLily Wang
dc.description.committeeLynne Seymour
dc.description.committeeWilliam P. McCormick
dc.description.committeeNicole Lazar


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