Robust Multiple Discriminant Rule Using Harrell-Davis\ Median Estimator: A Distribution-Free Approach to Cellwise-Casewise Outliers Coexistence
Multivariate data may be contaminated by cellwise and or casewise outliers. Cellwise outliers are individual data points within a variable that are extreme whereas casewise outliers are observations that come from a different distribution. Similar to other parametric methods, the Classical Multiple...
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Format: | Conference or Workshop Item |
Language: | English |
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2023
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Online Access: | https://repo.uum.edu.my/id/eprint/31055/1/ICOQSIA%202896%2001%202023%20050012-1-050012-7.pdf |
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author | Pang, Yik Siong Ahad, Nor Aishah Syed Yahaya, Sharipah Soaad Abdullah, Suhaida |
author_facet | Pang, Yik Siong Ahad, Nor Aishah Syed Yahaya, Sharipah Soaad Abdullah, Suhaida |
author_sort | Pang, Yik Siong |
collection | UUM |
description | Multivariate data may be contaminated by cellwise and or casewise outliers. Cellwise outliers are individual data points within a variable that are extreme whereas casewise outliers are observations that come from a different distribution. Similar to other parametric methods, the Classical Multiple Discriminant Rule (CMDR) achieve optimal performance only when the normality assumption is fulfilled. The coexistence of cellwise-casewise outliers can disrupt the data distribution of the sample. Thus, in order to alleviate the problem, this paper employed a distribution-free estimator, Harrell-Davis Median ,... together with Robust Covariance ... to construct Robust MDR (RMDRHD). The MDRs were evaluated based on misclassification rate via simulation study. The simulation results show that RMDR ... is able to achieve consistently lower misclassification rate than CMDR. Overall, the findings confirmed that the use of the distribution-free ... to robustify MDR is practical when dealing with both cellwise and casewise outliers |
first_indexed | 2024-10-01T01:43:36Z |
format | Conference or Workshop Item |
id | uum-31055 |
institution | Universiti Utara Malaysia |
language | English |
last_indexed | 2024-10-01T01:43:36Z |
publishDate | 2023 |
record_format | eprints |
spelling | uum-310552024-07-15T09:19:38Z https://repo.uum.edu.my/id/eprint/31055/ Robust Multiple Discriminant Rule Using Harrell-Davis\ Median Estimator: A Distribution-Free Approach to Cellwise-Casewise Outliers Coexistence Pang, Yik Siong Ahad, Nor Aishah Syed Yahaya, Sharipah Soaad Abdullah, Suhaida QA Mathematics Multivariate data may be contaminated by cellwise and or casewise outliers. Cellwise outliers are individual data points within a variable that are extreme whereas casewise outliers are observations that come from a different distribution. Similar to other parametric methods, the Classical Multiple Discriminant Rule (CMDR) achieve optimal performance only when the normality assumption is fulfilled. The coexistence of cellwise-casewise outliers can disrupt the data distribution of the sample. Thus, in order to alleviate the problem, this paper employed a distribution-free estimator, Harrell-Davis Median ,... together with Robust Covariance ... to construct Robust MDR (RMDRHD). The MDRs were evaluated based on misclassification rate via simulation study. The simulation results show that RMDR ... is able to achieve consistently lower misclassification rate than CMDR. Overall, the findings confirmed that the use of the distribution-free ... to robustify MDR is practical when dealing with both cellwise and casewise outliers 2023 Conference or Workshop Item PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/31055/1/ICOQSIA%202896%2001%202023%20050012-1-050012-7.pdf Pang, Yik Siong and Ahad, Nor Aishah and Syed Yahaya, Sharipah Soaad and Abdullah, Suhaida (2023) Robust Multiple Discriminant Rule Using Harrell-Davis\ Median Estimator: A Distribution-Free Approach to Cellwise-Casewise Outliers Coexistence. In: The 7th International Conference on Quantitative Sciences and its Applications (ICOQSIA2022), 22–24 August 2022, Sintok, Malaysia. https://doi.org/10.1063/5.0177243 |
spellingShingle | QA Mathematics Pang, Yik Siong Ahad, Nor Aishah Syed Yahaya, Sharipah Soaad Abdullah, Suhaida Robust Multiple Discriminant Rule Using Harrell-Davis\ Median Estimator: A Distribution-Free Approach to Cellwise-Casewise Outliers Coexistence |
title | Robust Multiple Discriminant Rule Using Harrell-Davis\ Median Estimator: A Distribution-Free Approach to Cellwise-Casewise Outliers Coexistence |
title_full | Robust Multiple Discriminant Rule Using Harrell-Davis\ Median Estimator: A Distribution-Free Approach to Cellwise-Casewise Outliers Coexistence |
title_fullStr | Robust Multiple Discriminant Rule Using Harrell-Davis\ Median Estimator: A Distribution-Free Approach to Cellwise-Casewise Outliers Coexistence |
title_full_unstemmed | Robust Multiple Discriminant Rule Using Harrell-Davis\ Median Estimator: A Distribution-Free Approach to Cellwise-Casewise Outliers Coexistence |
title_short | Robust Multiple Discriminant Rule Using Harrell-Davis\ Median Estimator: A Distribution-Free Approach to Cellwise-Casewise Outliers Coexistence |
title_sort | robust multiple discriminant rule using harrell davis median estimator a distribution free approach to cellwise casewise outliers coexistence |
topic | QA Mathematics |
url | https://repo.uum.edu.my/id/eprint/31055/1/ICOQSIA%202896%2001%202023%20050012-1-050012-7.pdf |
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