Nonparametric Comparison of Multiple Regression Curves in Scale-Space

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dc.contributor.authorPark, Cheolwooko
dc.contributor.authorHannig, Janko
dc.contributor.authorKang, Kee-Hoonko
dc.date.accessioned2021-06-11T01:30:29Z-
dc.date.available2021-06-11T01:30:29Z-
dc.date.created2021-06-11-
dc.date.created2021-06-11-
dc.date.issued2014-09-
dc.identifier.citationJOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, v.23, no.3, pp.657 - 677-
dc.identifier.issn1061-8600-
dc.identifier.urihttp://hdl.handle.net/10203/285756-
dc.description.abstractThis article concerns testing the equality of multiple curves in a nonparametric regression context. The proposed test forms an ANOVA type test statistic based on kernel smoothing and examines the ratio of between-and within-group variations. The empirical distribution of the test statistic is derived using a permutation test. Unlike traditional kernel smoothing approaches, the test is conducted in scale-space so that it does not require the selection of an optimal smoothing level, but instead considers a wide range of scales. The proposed method also visualizes its testing results as a color map and graphically summarizes the statistical differences between curves across multiple locations and scales. A numerical study using simulated and real examples is conducted to demonstrate the finite sample performance of the proposed method.-
dc.languageEnglish-
dc.publisherAMER STATISTICAL ASSOC-
dc.titleNonparametric Comparison of Multiple Regression Curves in Scale-Space-
dc.typeArticle-
dc.identifier.wosid000338205400004-
dc.identifier.scopusid2-s2.0-84925939472-
dc.type.rimsART-
dc.citation.volume23-
dc.citation.issue3-
dc.citation.beginningpage657-
dc.citation.endingpage677-
dc.citation.publicationnameJOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS-
dc.identifier.doi10.1080/10618600.2013.822816-
dc.contributor.localauthorPark, Cheolwoo-
dc.contributor.nonIdAuthorHannig, Jan-
dc.contributor.nonIdAuthorKang, Kee-Hoon-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorKernel smoothing-
dc.subject.keywordAuthorLocal constant estimator-
dc.subject.keywordAuthorPermutation test-
dc.subject.keywordAuthorSiZer map-
dc.subject.keywordAuthorVisualization-
dc.subject.keywordPlusTIME-SERIES-
dc.subject.keywordPlusSTATISTICAL-INFERENCE-
dc.subject.keywordPlusDENSITY-ESTIMATION-
dc.subject.keywordPlusADDITIVE-MODELS-
dc.subject.keywordPlusSIZER-
dc.subject.keywordPlusFEATURES-
dc.subject.keywordPlusVISUALIZATION-
dc.subject.keywordPlusEXPLORATION-
dc.subject.keywordPlusEQUALITY-
dc.subject.keywordPlusIMAGES-
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