Comparison of robust estimators for detecting outliers in multivariate datasets

Comparison of robust estimators for detecting outliers in multivariate datasets

Detecting outliers for multivariate data is difficult and does not work by visual inspection. Mahalanobis distance (MD) has been a classical method to detect outliers in multivariate data. However, classical mean and covariance matrix in MD suffer from masking and swamping effects. Masking effects h...

Full description

Saved in:
Bibliographic Details
Main Authors: Sharifah Sakinah, Syed Abd Mutalib, Siti Zanariah, Satari, Wan Nur Syahidah, Wan Yusoff
Format: Conference or Workshop Item
Language:English
Published: IOP Publishing 2021
Subjects:
Q Science (General)
QA Mathematics
Online Access:http://umpir.ump.edu.my/id/eprint/35199/1/Comparison%20of%20robust%20estimators%20for%20detecting%20outliers%20in%20multivariate%20datasets.pdf
http://umpir.ump.edu.my/id/eprint/35199/
https://doi.org/10.1088/1742-6596/1988/1/012095
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Malaysia Pahang
Language: English

Internet

http://umpir.ump.edu.my/id/eprint/35199/1/Comparison%20of%20robust%20estimators%20for%20detecting%20outliers%20in%20multivariate%20datasets.pdf
http://umpir.ump.edu.my/id/eprint/35199/
https://doi.org/10.1088/1742-6596/1988/1/012095

Similar Items