On robust estimation for slope in linear functional relationship model

In this paper, we propose a robust parameter estimation method for the linear functional relationship model. We improved the maximum likelihood estimation using robust estimators and robust correlation coefficients to estimate the slope parameter. The performance of the propose method, MMLE, is comp...

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Main Authors: Azuraini Mohd Arif, Yong Zulina Zubairi, Abdul Ghapor Hussin
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2019
Online Access:http://journalarticle.ukm.my/13073/
http://journalarticle.ukm.my/13073/1/27%20Azuraini%20Mohd%20Arif.pdf
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author Azuraini Mohd Arif,
Yong Zulina Zubairi,
Abdul Ghapor Hussin,
author_facet Azuraini Mohd Arif,
Yong Zulina Zubairi,
Abdul Ghapor Hussin,
author_sort Azuraini Mohd Arif,
building UKM Institutional Repository
collection Online Access
description In this paper, we propose a robust parameter estimation method for the linear functional relationship model. We improved the maximum likelihood estimation using robust estimators and robust correlation coefficients to estimate the slope parameter. The performance of the propose method, MMLE, is compared with the standard maximum likelihood estimation (MLE) and the nonparametric method in terms of mean square error. The results for simulation studies suggested the performance of the MMLE and nonparametric methods gives better estimate than the standard MLE in the presence of outliers. The novelty of the proposed method is that it is not affected by the presence of outliers and is simple to use. To illustrate practical application of the methods, we obtain the estimate of the slope parameter in a study of body-composition techniques for children.
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spelling oai:generic.eprints.org:130732019-06-20T14:57:01Z http://journalarticle.ukm.my/13073/ On robust estimation for slope in linear functional relationship model Azuraini Mohd Arif, Yong Zulina Zubairi, Abdul Ghapor Hussin, In this paper, we propose a robust parameter estimation method for the linear functional relationship model. We improved the maximum likelihood estimation using robust estimators and robust correlation coefficients to estimate the slope parameter. The performance of the propose method, MMLE, is compared with the standard maximum likelihood estimation (MLE) and the nonparametric method in terms of mean square error. The results for simulation studies suggested the performance of the MMLE and nonparametric methods gives better estimate than the standard MLE in the presence of outliers. The novelty of the proposed method is that it is not affected by the presence of outliers and is simple to use. To illustrate practical application of the methods, we obtain the estimate of the slope parameter in a study of body-composition techniques for children. Penerbit Universiti Kebangsaan Malaysia 2019-01 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/13073/1/27%20Azuraini%20Mohd%20Arif.pdf Azuraini Mohd Arif, and Yong Zulina Zubairi, and Abdul Ghapor Hussin, (2019) On robust estimation for slope in linear functional relationship model. Sains Malaysiana, 48 (1). pp. 237-242. ISSN 0126-6039 http://www.ukm.my/jsm/malay_journals/jilid48bil1_2019/KandunganJilid48Bil1_2019.html
spellingShingle Azuraini Mohd Arif,
Yong Zulina Zubairi,
Abdul Ghapor Hussin,
On robust estimation for slope in linear functional relationship model
title On robust estimation for slope in linear functional relationship model
title_full On robust estimation for slope in linear functional relationship model
title_fullStr On robust estimation for slope in linear functional relationship model
title_full_unstemmed On robust estimation for slope in linear functional relationship model
title_short On robust estimation for slope in linear functional relationship model
title_sort on robust estimation for slope in linear functional relationship model
url http://journalarticle.ukm.my/13073/
http://journalarticle.ukm.my/13073/
http://journalarticle.ukm.my/13073/1/27%20Azuraini%20Mohd%20Arif.pdf