A Review on Outliers-Detection Methods for Multivariate Data

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Sharifah Sakinah Syed Abd Mutalib
Siti Zanariah Satari
Wan Nur Syahidah Wan Yusoff


Data in practice are often of high dimension and multivariate in nature. Detection of outliers has been one of the problems in multivariate analysis. Detecting outliers in multivariate data is difficult and it is not sufficient by using only graphical inspection. In this paper, a nontechnical and brief outlier detection method for multivariate data which are projection pursuit method, methods based on robust distance and cluster analysis are reviewed. The strengths and weaknesses of each method are briefly discussed.


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Syed Abd Mutalib, S. S. ., Satari, S. Z., & Wan Yusoff, W. N. S. (2021). A Review on Outliers-Detection Methods for Multivariate Data. Journal of Statistical Modeling &Amp; Analytics (JOSMA), 3(1). https://doi.org/10.22452/josma.vol3no1.1