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A Comparison Study for Ordination Methods in Ecology

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dc.contributor.authorKo, Hyeon-Seok-
dc.contributor.authorJhun, Myoungshic-
dc.contributor.authorJeong, Hyeong Chul-
dc.date.accessioned2021-09-04T19:43:27Z-
dc.date.available2021-09-04T19:43:27Z-
dc.date.created2021-06-15-
dc.date.issued2015-02-
dc.identifier.issn1225-066X-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/94556-
dc.description.abstractVarious kinds of ordination methods such as correspondence analysis and canonical correspondence analysis are used in community ecology to visualize relationships among species, sites, and environmental variables. Ter Braak (1986), Jackson and Somers (1991), Parmer (1993), compared the ordination methods using eigenvalue and distance graph. However, these methods did not show the relationship between population and biplot because they are only based on surveyed data. In this paper, a method that measures the extent to show population information to biplot was introduced to compare ordination methods objectively.-
dc.languageKorean-
dc.language.isoko-
dc.publisherKOREAN STATISTICAL SOC-
dc.titleA Comparison Study for Ordination Methods in Ecology-
dc.typeArticle-
dc.contributor.affiliatedAuthorJhun, Myoungshic-
dc.identifier.doi10.5351/KJAS.2015.28.1.049-
dc.identifier.wosid000437594300005-
dc.identifier.bibliographicCitationKOREAN JOURNAL OF APPLIED STATISTICS, v.28, no.1, pp.49 - 60-
dc.relation.isPartOfKOREAN JOURNAL OF APPLIED STATISTICS-
dc.citation.titleKOREAN JOURNAL OF APPLIED STATISTICS-
dc.citation.volume28-
dc.citation.number1-
dc.citation.startPage49-
dc.citation.endPage60-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.identifier.kciidART001964827-
dc.description.journalClass2-
dc.description.journalRegisteredClasskci-
dc.relation.journalResearchAreaMathematics-
dc.relation.journalWebOfScienceCategoryStatistics & Probability-
dc.subject.keywordAuthorDistance graph-
dc.subject.keywordAuthorprincipal component analysis-
dc.subject.keywordAuthorcorrespondence analysis-
dc.subject.keywordAuthorredundancy analysis-
dc.subject.keywordAuthorcanonical correspondence analysis-
dc.subject.keywordAuthorcanonical ordination analysis-
dc.subject.keywordAuthorsingular value decomposition-
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