Please use this identifier to cite or link to this item: http://hdl.handle.net/11328/755
Title: Detection of outliers in multivariate data: a method based on clustering and robust estimators.
Authors: Santos-Pereira, Carla
Pires, Ana M.
Keywords: Multivariate analysis
Outlier detection
Robust estimation
Clustering
Supervised classification
Issue Date: 2002
Citation: Santos-Pereira, C., & Pires, A.M. (2002). Detection of outliers in multivariate data: a method based on clustering and robust estimators. In W. Hordle, & B. Ronz,(editors), Proceedings in Computational Statistics (pp.291-296), COMSTAT, Barcelona.
Description: Outlier identification is important in many applications in multivariate analysis. Either because there is some specific interest in finding anomalous observations or as a pre-processing task before the application of multivariate method in order to preserve the results from possible harmful effects of those observations. [...]
URI: http://hdl.handle.net/11328/755
Appears in Collections:REMIT - Comunicações a Congressos Internacionais / Papers in International Meetings

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