Detecting multiple outliers in linear regression using a cluster method combined with graphical visualization

摘要

This paper provides a graphical visualization of multiple outliers based on a clustering algorithm using the minimal spanning tree, and proposes a modified version of this clustering algorithm for identifying multiple outliers. Graphical visualization is helpful for the classification of multiple outliers. It is shown that the proposed modified procedure preserves the performance of the clustering algorithm in identifying multiple outliers, but also reduces the problem of swamping of observations.