SiZer analysis for the comparison of time series

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dc.contributor.authorPark, Cheolwooko
dc.contributor.authorVaughan, Amyko
dc.contributor.authorHannig, Janko
dc.contributor.authorKang, Kee-Hoonko
dc.date.accessioned2021-06-11T01:50:36Z-
dc.date.available2021-06-11T01:50:36Z-
dc.date.created2021-06-11-
dc.date.created2021-06-11-
dc.date.issued2009-12-
dc.identifier.citationJOURNAL OF STATISTICAL PLANNING AND INFERENCE, v.139, no.12, pp.3974 - 3988-
dc.identifier.issn0378-3758-
dc.identifier.urihttp://hdl.handle.net/10203/285782-
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. (C) 2009 Elsevier B.V. All rights reserved.-
dc.languageEnglish-
dc.publisherELSEVIER SCIENCE BV-
dc.titleSiZer analysis for the comparison of time series-
dc.typeArticle-
dc.identifier.wosid000270316000003-
dc.identifier.scopusid2-s2.0-69249203517-
dc.type.rimsART-
dc.citation.volume139-
dc.citation.issue12-
dc.citation.beginningpage3974-
dc.citation.endingpage3988-
dc.citation.publicationnameJOURNAL OF STATISTICAL PLANNING AND INFERENCE-
dc.identifier.doi10.1016/j.jspi.2009.05.003-
dc.contributor.localauthorPark, Cheolwoo-
dc.contributor.nonIdAuthorVaughan, Amy-
dc.contributor.nonIdAuthorHannig, Jan-
dc.contributor.nonIdAuthorKang, Kee-Hoon-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorComparison of multiple time series-
dc.subject.keywordAuthorLocal linear smoothing-
dc.subject.keywordAuthorMultiple testing adjustment-
dc.subject.keywordAuthorBandwidth-
dc.subject.keywordAuthorAutocovariance function-
dc.subject.keywordAuthorWeak convergence-
dc.subject.keywordPlusNONPARAMETRIC REGRESSION-CURVES-
dc.subject.keywordPlusLONG MEMORY ERRORS-
dc.subject.keywordPlusEQUALITY-
dc.subject.keywordPlusFEATURES-
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