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Projection pursuit algorithms to detect outliers.
- Source :
-
Cuadernos de Administración (01203592) . 2020, Vol. 33, p1-15. 15p. - Publication Year :
- 2020
-
Abstract
- In this paper, we compare the methods proposed by Peña and Prieto (2001), and Filzmoser, Maronna, and Werner (2008) to detect outliers in a set of Argentine companies that quote their shares in the Stock Exchange. A significant heterogeneity between observations can be a consequence of the presence of outliers. The detection of outliers is an important task for the statistical analysis since they distort descriptive measures and parameters estimators. There are different multivariate methods to detect outliers, such as distance-based methods and projection pursuit methods. [ABSTRACT FROM AUTHOR]
- Subjects :
- *OUTLIER detection
*STOCK exchanges
*TASK analysis
*STATISTICS
Subjects
Details
- Language :
- English
- ISSN :
- 01203592
- Volume :
- 33
- Database :
- Academic Search Index
- Journal :
- Cuadernos de Administración (01203592)
- Publication Type :
- Academic Journal
- Accession number :
- 144399652
- Full Text :
- https://doi.org/10.11144/Javeriana.cao33.ppado