A Procedure for Detecting a Pair of Outliers in Multivariate Dataset

B. K. Nkansah, B. K. Gordor


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


Multiple Outlier Detection; Outlier Displaying Component

Full Text:


DOI: http://dx.doi.org/10.3968/j.sms.1923845220120402.1623


  • There are currently no refbacks.

Share us to:   


If you have already registered in Journal A and plan to submit article(s) to Journal B, please click the CATEGORIES, or JOURNALS A-Z on the right side of the "HOME".

We only use three mailboxes as follows to deal with issues about paper acceptance, payment and submission of electronic versions of our journals to databases:
caooc@hotmail.com; sms@cscanada.net; sms@cscanada.org

 Articles published in Studies in Mathematical Sciences are licensed under Creative Commons Attribution 4.0 (CC-BY).


Address: 9375 Rue de Roissy Brossard, Québec, J4X 3A1, Canada

Telephone: 1-514-558 6138

Copyright © 2010 Canadian Research & Development Centre of Sciences and Cultures