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REPPlab: An R package for detecting clusters and outliers using exploratory projection pursuit

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dc.contributor.authorFischer, Daniel
dc.contributor.authorBerro, Alain
dc.contributor.authorNordhausen, Klaus
dc.contributor.authorRuiz-Gazen, Anne
dc.contributor.departmentid4100111010-
dc.contributor.otherUniversity of Toulouse Capitole-
dc.contributor.otherVienna University of Technology-
dc.date.accessioned2019-08-15T09:25:30Z
dc.date.accessioned2025-05-28T12:38:12Z
dc.date.available2019-08-15T09:25:30Z
dc.date.issued2019
dc.description.vuosik2019
dc.format.bitstreamfalse
dc.format.extent23 p.-
dc.identifier.olddbid487020
dc.identifier.oldhandle10024/544493
dc.identifier.urihttps://jukuri.luke.fi/handle/11111/22784
dc.language.isoeng-
dc.okm.corporatecopublicationei-
dc.okm.discipline113-
dc.okm.internationalcopublicationon-
dc.okm.openaccess0 = Ei vastausta-
dc.okm.selfarchivedei-
dc.publisherTaylor & Francis-
dc.relation.doi10.1080/03610918.2019.1626880-
dc.relation.ispartofseriesCommunications in Statistics - Simulation and Computation-
dc.relation.issn0361-0918-
dc.source.identifierhttps://jukuri.luke.fi/handle/10024/544493
dc.subject.agrovocJava-
dc.subject.agrovocTribes-
dc.subject.keywordGenetic algorithms-
dc.subject.keywordKurtosis-
dc.subject.keywordParticle swarm optimization-
dc.subject.keywordProjection index-
dc.subject.keywordProjection matrix-
dc.subject.keywordUnsupervised data analysis-
dc.titleREPPlab: An R package for detecting clusters and outliers using exploratory projection pursuit-
dc.type.okmfi=A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä|sv=A1 Originalartikel i en vetenskaplig tidskrift|en=A1 Journal article (refereed), original research|-

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