Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/62075

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dc.contributor.authorFachada, Nunopor
dc.contributor.authorRodrigues, Joãopor
dc.contributor.authorLopes, Vitor V.por
dc.contributor.authorMartins, Rui C.por
dc.contributor.authorRosa, Agostinho C.por
dc.date.accessioned2019-11-13T13:52:33Z-
dc.date.issued2016-03-22-
dc.identifier.issn2073-4859por
dc.identifier.urihttps://hdl.handle.net/1822/62075-
dc.description.abstractThe R package micompr implements a procedure for assessing if two or more multivariate samples are drawn from the same distribution. The procedure uses principal component analysis to convert multivariate observations into a set of linearly uncorrelated statistical measures, which are then compared using a number of statistical methods. This technique is independent of the distributional properties of samples and automatically selects features that best explain their differences. The procedure is appropriate for comparing samples of time series, images, spectrometric measures or similar high-dimension multivariate observations.por
dc.description.sponsorshipThis work was supported by the Fundacao para a Ciencia e a Tecnologia (FCT) projects UID/EEA/50009/2013 and UID/MAT/04561/2013, and partially funded with grant SFRH/BD/48310/2008, also from FCT.por
dc.language.isoengpor
dc.publisherThe R Foundationpor
dc.rightsrestrictedAccesspor
dc.titlemicompr: an R package for multivariate independent comparison of observationspor
dc.typearticlepor
dc.peerreviewedyespor
oaire.citationStartPage405por
oaire.citationEndPage420por
oaire.citationIssue2por
oaire.citationVolume8por
dc.identifier.eissn2073-4859-
dc.date.embargo10000-01-01-
dc.subject.wosScience & Technologypor
sdum.journalThe R Journalpor
Aparece nas coleções:ICVS - Artigos em revistas internacionais / Papers in international journals

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