Journal of Applied & Computational Mathematics

ISSN: 2168-9679

Open Access

A study on Methods to Handle Outliers in Multivariate


Wei Guangwei

Detecting outliers is an integral part of data analysis that sheds light on points that do not conform to the rest of the data. Whereas in univariate data, outliers appear at the extremes of the ordered sample, in the multivariate case they may be defined in many ways and are not generally based on an assumed statistical model. We present here methods for detecting multivariate outliers based on various definitions and illustrate their features by applying them to two sets of data. No single approach can be recommended over others, since each one aims at detecting outliers of a particular kind.


Share this article

Google Scholar citation report
Citations: 1282

Journal of Applied & Computational Mathematics received 1282 citations as per Google Scholar report

Journal of Applied & Computational Mathematics peer review process verified at publons

Indexed In

arrow_upward arrow_upward