Robust Correlation Procedure via Sn Estimator
Pearson correlation coefficient is the most widely used statistical technique when measuring a relationship between the bivariate normal distribution when the assumptions are fulfilled. However, this classical correlation coefficient performs poor in the presence of an outlier. Therefore, this study...
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Universiti Teknikal Malaysia Melaka
2018
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my.uum.repo.310542024-07-15T09:18:33Z https://repo.uum.edu.my/id/eprint/31054/ Robust Correlation Procedure via Sn Estimator Ahad, Nor Aishah Zakaria, Nur Amira Abdullah, Suhaida Syed Yahaya, Sharipah Soaad Yusof, Norhayati QA Mathematics Pearson correlation coefficient is the most widely used statistical technique when measuring a relationship between the bivariate normal distribution when the assumptions are fulfilled. However, this classical correlation coefficient performs poor in the presence of an outlier. Therefore, this study aims to propose a new version of robust correlation coefficient based on robust scale estimator Sn. The performance of the proposed robust correlation coefficient is assessed based on correlation value, average bias and standard error. The performance of the proposed coefficient is compared with the classical correlation together with the existing robust correlation coefficient. Classical correlation coefficient performs well under the condition of perfect data. However, its performance becomes worst when data is contaminated. Under the condition of data contamination, robust correlation coefficient performed better compared to classical correlation Universiti Teknikal Malaysia Melaka 2018 Article PeerReviewed application/pdf en cc4_by_nc_nd https://repo.uum.edu.my/id/eprint/31054/1/JTECE%2010%201-10%202018%20115-118.pdf Ahad, Nor Aishah and Zakaria, Nur Amira and Abdullah, Suhaida and Syed Yahaya, Sharipah Soaad and Yusof, Norhayati (2018) Robust Correlation Procedure via Sn Estimator. Journal of Telecommunication, Electronic and Computer Engineering, 10 (1-10). pp. 115-118. ISSN 2289-8131 https://jtec.utem.edu.my/jtec/article/view/3801 https://jtec.utem.edu.my/jtec/article/view/3801 https://jtec.utem.edu.my/jtec/article/view/3801 |
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QA Mathematics Ahad, Nor Aishah Zakaria, Nur Amira Abdullah, Suhaida Syed Yahaya, Sharipah Soaad Yusof, Norhayati Robust Correlation Procedure via Sn Estimator |
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Pearson correlation coefficient is the most widely used statistical technique when measuring a relationship between the bivariate normal distribution when the assumptions are fulfilled. However, this classical correlation coefficient performs poor in the presence of an outlier. Therefore, this study aims to propose a new version of robust correlation coefficient based on robust scale estimator Sn. The performance of the proposed robust correlation coefficient is assessed based on correlation value, average bias and standard error. The performance of the proposed coefficient is compared with the classical correlation together with the existing robust correlation coefficient. Classical correlation coefficient performs well under the condition of perfect data. However, its performance becomes worst when data is contaminated. Under the condition of data contamination, robust correlation coefficient performed better compared to classical correlation |
format |
Article |
author |
Ahad, Nor Aishah Zakaria, Nur Amira Abdullah, Suhaida Syed Yahaya, Sharipah Soaad Yusof, Norhayati |
author_facet |
Ahad, Nor Aishah Zakaria, Nur Amira Abdullah, Suhaida Syed Yahaya, Sharipah Soaad Yusof, Norhayati |
author_sort |
Ahad, Nor Aishah |
title |
Robust Correlation Procedure via Sn Estimator |
title_short |
Robust Correlation Procedure via Sn Estimator |
title_full |
Robust Correlation Procedure via Sn Estimator |
title_fullStr |
Robust Correlation Procedure via Sn Estimator |
title_full_unstemmed |
Robust Correlation Procedure via Sn Estimator |
title_sort |
robust correlation procedure via sn estimator |
publisher |
Universiti Teknikal Malaysia Melaka |
publishDate |
2018 |
url |
https://repo.uum.edu.my/id/eprint/31054/1/JTECE%2010%201-10%202018%20115-118.pdf https://jtec.utem.edu.my/jtec/article/view/3801 https://repo.uum.edu.my/id/eprint/31054/ https://jtec.utem.edu.my/jtec/article/view/3801 https://jtec.utem.edu.my/jtec/article/view/3801 |
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