✦ LIBER ✦

Robust bivariate boxplots and multiple outlier detection

✍ Scribed by Sergio Zani; Marco Riani; Aldo Corbellini

Book ID: 104306793
Publisher: Elsevier Science
Year: 1998
Tongue: English
Weight: 777 KB
Volume: 28
Category: Article
ISSN: 0167-9473
DOI: 10.1016/s0167-9473(98)00040-1

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✦ Synopsis

In this paper we suggest a simple way of constructing a bivariate boxplot based on convex hull peeling and B-spline smoothing. The proposed method shows some advantages with respect to that suggested by Goldberg and Iglewicz (1992). Our approach leads to defining a natural inner region which is completely nonparametric and smooth. Furthermore it retains the correlation in the observations and adapts to differing spread of the data in the different directions. The outer contour, which is based on a multiple of the distance of the inner region from the centre, is robust to the presence of clusters of outliers. We also show how the construction of a bivariate boxplot for each pair of variables can become a very useful tool for the detection of multivariate outliers.

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