Statistical inference and visualization in scale-space for spatially dependent images

Cited 9 time in webofscience Cited 0 time in scopus
  • Hit : 41
  • Download : 0
DC FieldValueLanguage
dc.contributor.authorVaughan, Amyko
dc.contributor.authorJun, Mikyoungko
dc.contributor.authorPark, Cheolwooko
dc.date.accessioned2021-06-11T01:50:26Z-
dc.date.available2021-06-11T01:50:26Z-
dc.date.created2021-06-11-
dc.date.created2021-06-11-
dc.date.issued2012-03-
dc.identifier.citationJOURNAL OF THE KOREAN STATISTICAL SOCIETY, v.41, no.1, pp.115 - 135-
dc.identifier.issn1226-3192-
dc.identifier.urihttp://hdl.handle.net/10203/285778-
dc.description.abstractSiZer (Significant ZERo crossing of the derivatives) is a graphical scale-space visualization tool that allows for statistical inferences. In this paper we develop a spatial SiZer for finding significant features and conducting goodness-of-fit tests for spatially dependent images. The spatial SiZer utilizes a family of kernel estimates of the image and provides not only exploratory data analysis but also statistical inference with spatial correlation taken into account. It is also capable of comparing the observed image with a specific null model being tested by adjusting the statistical inference using an assumed covariance structure. Pixel locations having statistically significant differences between the image and a given null model are highlighted by arrows. The spatial SiZer is compared with the existing independent SiZer via the analysis of simulated data with and without signal on both planar and spherical domains. We apply the spatial SiZer method to the decadal temperature change over some regions of the Earth. (C) 2011 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.-
dc.languageEnglish-
dc.publisherKOREAN STATISTICAL SOC-
dc.titleStatistical inference and visualization in scale-space for spatially dependent images-
dc.typeArticle-
dc.identifier.wosid000300744700011-
dc.identifier.scopusid2-s2.0-84856528951-
dc.type.rimsART-
dc.citation.volume41-
dc.citation.issue1-
dc.citation.beginningpage115-
dc.citation.endingpage135-
dc.citation.publicationnameJOURNAL OF THE KOREAN STATISTICAL SOCIETY-
dc.identifier.doi10.1016/j.jkss.2011.07.006-
dc.contributor.localauthorPark, Cheolwoo-
dc.contributor.nonIdAuthorVaughan, Amy-
dc.contributor.nonIdAuthorJun, Mikyoung-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
dc.subject.keywordAuthorGoodness-of-fit test-
dc.subject.keywordAuthorImage data analysis-
dc.subject.keywordAuthorKernel smoothing-
dc.subject.keywordAuthorScale-space-
dc.subject.keywordAuthorSpatial correlation-
dc.subject.keywordAuthorStatistical significance-
dc.subject.keywordPlusTIME-SERIES-
dc.subject.keywordPlusDENSITY-ESTIMATION-
dc.subject.keywordPlusSIZER-
dc.subject.keywordPlusFEATURES-
dc.subject.keywordPlusMODELS-
dc.subject.keywordPlusEXPLORATION-
dc.subject.keywordPlusCURVES-
Appears in Collection
MA-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 9 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0