Ahad, Nor Aishah and Pang, Yik Siong and Syed Yahaya, Sharipah Soaad and Abdullah, Suhaida (2022) Robust Multiple Discriminant Rule with Hodges-Lehmann in Handling Equal Proportion of Cellwise-Casewise Outliers. In: The 7th International Conference on Quantitative Sciences and its Applications (ICOQSIA2022), 22–24 August 2022, Sintok, Malaysia.

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Abstract

The presence of outliers in a dataset can cause the outcome of classical statistical tools to be inaccurate. Especially in a multivariate context, where researchers have to deal with either or both cellwise and casewise outliers. This study investigated the accuracy of the Multiple Discriminant Rule (MDR) when both cellwise and casewise outliers exist in a proportionate manner. Classical MDR (CMDR) was constructed using the classical sample mean ... and sample covariance (S) while Robust MDR (RMDR..) was constructed using the Hodges-Lehmann estimator ... and Robust Covariance ... The simulation was carried out where cellwise outliers were shifted in location value and casewise outliers were involved with location, covariance and dual influence. Based on the simulation results, despite the performance of both CMDR and RMDR.. being quite close when dealing with cellwise-location and casewise-location outliers, RMDR.. outperformed CMDR in both cellwise-location and casewise-covariance as well as cellwise-location and casewise-dual conditions. In summary, the use of ... in robustifying MDR was competent even though dealing with outliers percentage beyond its tolerance

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	Online ISSN 1551-7616 Print ISSN 0094-243X
Uncontrolled Keywords:	Cellwise Outliers, Casewise Outliers, Hodges-Lehmann Estimator
Subjects:	Q Science > QA Mathematics
Divisions:	School of Quantitative Sciences
Depositing User:	Mdm. Sarkina Mat Saad @ Shaari
Date Deposited:	15 Jul 2024 09:20
Last Modified:	15 Jul 2024 09:20
URI:	https://repo.uum.edu.my/id/eprint/31056

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