TY - JOUR AU - Syed Abd Mutalib, Sharifah Sakinah AU - Satari, Siti Zanariah AU - Wan Yusoff, Wan Nur Syahidah PY - 2021/06/29 Y2 - 2024/03/29 TI - A Review on Outliers-Detection Methods for Multivariate Data JF - Journal of Statistical Modeling & Analytics (JOSMA) JA - JOSMA VL - 3 IS - 1 SE - Articles DO - 10.22452/josma.vol3no1.1 UR - https://ejournal.um.edu.my/index.php/JOSMA/article/view/30586 SP - AB - <p>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.</p> ER -