A review on outliers-detection methods for multivariate data

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 br...

Full description

Bibliographic Details
Main Authors: Sharifah Sakinah, Syed Abd Mutalib, Siti Zanariah, Satari, Wan Nur Syahidah, Wan Yusoff
Format: Article
Language:English
English
Published: Institute of Statistics Malaysia (ISMy) 2021
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/31672/
http://umpir.ump.edu.my/id/eprint/31672/1/30586
http://umpir.ump.edu.my/id/eprint/31672/2/2021%20Abd%20Mutalib%20et%20al%20JOSMA.pdf
_version_ 1848823827124977664
author Sharifah Sakinah, Syed Abd Mutalib
Siti Zanariah, Satari
Wan Nur Syahidah, Wan Yusoff
author_facet Sharifah Sakinah, Syed Abd Mutalib
Siti Zanariah, Satari
Wan Nur Syahidah, Wan Yusoff
author_sort Sharifah Sakinah, Syed Abd Mutalib
building UMP Institutional Repository
collection Online Access
description 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.
first_indexed 2025-11-15T03:03:19Z
format Article
id ump-31672
institution Universiti Malaysia Pahang
institution_category Local University
language English
English
last_indexed 2025-11-15T03:03:19Z
publishDate 2021
publisher Institute of Statistics Malaysia (ISMy)
recordtype eprints
repository_type Digital Repository
spelling ump-316722021-07-19T07:23:11Z http://umpir.ump.edu.my/id/eprint/31672/ A review on outliers-detection methods for multivariate data Sharifah Sakinah, Syed Abd Mutalib Siti Zanariah, Satari Wan Nur Syahidah, Wan Yusoff QA Mathematics 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. Institute of Statistics Malaysia (ISMy) 2021-07-01 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/31672/1/30586 pdf en http://umpir.ump.edu.my/id/eprint/31672/2/2021%20Abd%20Mutalib%20et%20al%20JOSMA.pdf Sharifah Sakinah, Syed Abd Mutalib and Siti Zanariah, Satari and Wan Nur Syahidah, Wan Yusoff (2021) A review on outliers-detection methods for multivariate data. ournal of Statistical Modeling and Analytics, 3 (1). pp. 1-15. (Published) https://doi.org/10.22452/josma.vol3no1.1
spellingShingle QA Mathematics
Sharifah Sakinah, Syed Abd Mutalib
Siti Zanariah, Satari
Wan Nur Syahidah, Wan Yusoff
A review on outliers-detection methods for multivariate data
title A review on outliers-detection methods for multivariate data
title_full A review on outliers-detection methods for multivariate data
title_fullStr A review on outliers-detection methods for multivariate data
title_full_unstemmed A review on outliers-detection methods for multivariate data
title_short A review on outliers-detection methods for multivariate data
title_sort review on outliers-detection methods for multivariate data
topic QA Mathematics
url http://umpir.ump.edu.my/id/eprint/31672/
http://umpir.ump.edu.my/id/eprint/31672/
http://umpir.ump.edu.my/id/eprint/31672/1/30586
http://umpir.ump.edu.my/id/eprint/31672/2/2021%20Abd%20Mutalib%20et%20al%20JOSMA.pdf