A performance evaluation in multivariate outliers identification methods.

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dc.contributor.authorBarbosa, Josino José
dc.contributor.authorDuarte, Anderson Ribeiro
dc.contributor.authorMartins, Helgem de Souza Ribeiro
dc.date.accessioned2022-03-03T18:37:49Z
dc.date.available2022-03-03T18:37:49Z
dc.date.issued2019pt_BR
dc.description.abstractMethodologies for identifying multivariate outliers are extremely important in statistical analysis. Outliers may reveal relevant information to variables under investigation. Statistical applications without prior identification of possible extreme values may yield controversial results and induce mistaken decision making. In many contexts, outliers are points of great practical interest. Given this, this paper seeks to discuss methodologies for the detection of multivariate outliers through a fair and adequate comparative technique in their simulation procedure. The comparison considers detection techniques based on Mahalanobis distance, besides a methodology based on cluster analysis technique. Sensitivity, specificity, and accuracy metrics are used to measure the method quality. An analysis of the computational time required to perform the procedures is evaluated. The technique based on cluster analysis revealed a noticeable superiority over the others in detection quality and also in execution time.pt_BR
dc.identifier.citationBARBOSA, J. J.; DUARTE, A. R.; MARTINS, H. de S. R. A performance evaluation in multivariate outliers identification methods. Ciência e Natura, Santa Maria, v. 42, 2019. Disponível em: <https://periodicos.ufsm.br/cienciaenatura/article/view/41662>. Acesso em: 25 ago. 2021.pt_BR
dc.identifier.doihttps://doi.org/10.5902/2179460X41662pt_BR
dc.identifier.issn2179-460X
dc.identifier.urihttp://www.repositorio.ufop.br/jspui/handle/123456789/14617
dc.language.isoen_USpt_BR
dc.rightsabertopt_BR
dc.rights.licenseThis work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Fonte: o PDF do artigo.pt_BR
dc.subjectSimulationpt_BR
dc.subjectCluster analysispt_BR
dc.subjectAccuracypt_BR
dc.subjectComputational timept_BR
dc.titleA performance evaluation in multivariate outliers identification methods.pt_BR
dc.typeArtigo publicado em periodicopt_BR
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