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A Procedure for Detecting a Pair of Outliers in Multivariate Dataset

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Author(s): B. K. Nkansah | B. K. Gordor

Journal: Studies in Mathematical Sciences
ISSN 1923-8444

Volume: 4;
Issue: 2;
Start page: 1;
Date: 2012;
Original page

Keywords: Multiple Outlier Detection | Outlier Displaying Component

ABSTRACT
The paper presents a procedure for detecting a pair of outliers in multivariate data. The procedure involves a reduction of the dimensionality of the dataset to only two dimensions along outlier displaying components, and then determines the orientation of a least squares ellipse that fits the scatter of points of the two dimensional dataset. Finally, the reduced data is projected unto a vector which is determined in terms of the orientation of the ellipse. The results show that if two observations constitute a pair of outliers in a data set, then the pair is extreme at either ends of the one-dimensional projection and separated clearly from the remaining observations. If the two outliers are not distinct on such a one-dimensional projection, three key rules are prescribed for successful determination of the right pair of outliers.Key words: Multiple Outlier Detection; Outlier Displaying Component
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