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dc.contributor.authorFachada N
dc.contributor.authorRodrigues J
dc.contributor.authorLopes V.V
dc.contributor.authorMartins R.C
dc.contributor.authorRosa A.C.
dc.date.accessioned2021-03-17T18:06:34Z
dc.date.available2021-03-17T18:06:34Z
dc.date.issued2016-11-21
dc.identifier.issn2073-4859es_PE
dc.identifier.urihttps://hdl.handle.net/20.500.12815/214
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.es_PE
dc.formatapplication/pdfes_PE
dc.language.isoenges_PE
dc.publisherThe R Foundation for Statistical Computinges_PE
dc.rightsinfo:eu-repo/semantics/openAccesses_PE
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceRepositorio Institucional UTECes_PE
dc.sourceUniversidad de Ingeniería y Tecnología - UTECes_PE
dc.subjectMicompres_PE
dc.subjectveganes_PE
dc.subjectBlossomes_PE
dc.subjectEnergyes_PE
dc.subjectCrossmatches_PE
dc.subjectCrameres_PE
dc.subjectChemoSpeces_PE
dc.subjectBiotoolses_PE
dc.subjectTestthates_PE
dc.subjectKnitres_PE
dc.subjectRoxygen2es_PE
dc.subjectDeseasonalizees_PE
dc.titleMicompr: An r package for multivariate independent comparison of observationses_PE
dc.typeinfo:eu-repo/semantics/articlees_PE
dc.identifier.doihttps://doi.org/10.32614/rj-2016-055es_PE
dc.identifier.journalThe R Journales_PE


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