Multiple outliers detection procedures in linear regression

This paper describes a procedure for identifying multiple outliers in linear regression. This procedure uses a robust fit which is the least of trimmed of squares (LTS) and the single linkage clustering method to obtain the potential outliers. Then multiple-case diagnostics are used to obtain the ou...

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Main Authors: Adnan, Robiah, Mohamad, Mohd Nor, Setan, Halim
Format: Article
Language:English
Published: Faculty of Science 2003
Subjects:
Online Access:http://eprints.utm.my/1193/
http://eprints.utm.my/1193/1/RobiahAdnan2003_MultipleOutliersDetectionProcedures.pdf
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author Adnan, Robiah
Mohamad, Mohd Nor
Setan, Halim
author_facet Adnan, Robiah
Mohamad, Mohd Nor
Setan, Halim
author_sort Adnan, Robiah
building UTeM Institutional Repository
collection Online Access
description This paper describes a procedure for identifying multiple outliers in linear regression. This procedure uses a robust fit which is the least of trimmed of squares (LTS) and the single linkage clustering method to obtain the potential outliers. Then multiple-case diagnostics are used to obtain the outliers from these potential outliers. The performance of this procedure is also compared to Serbert's method. Monte Carlo simulations are used in determining which procedure performed best in all of the linear regression scenarios
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institution Universiti Teknologi Malaysia
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publishDate 2003
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spelling utm-11932010-08-13T01:38:07Z http://eprints.utm.my/1193/ Multiple outliers detection procedures in linear regression Adnan, Robiah Mohamad, Mohd Nor Setan, Halim TA Engineering (General). Civil engineering (General) This paper describes a procedure for identifying multiple outliers in linear regression. This procedure uses a robust fit which is the least of trimmed of squares (LTS) and the single linkage clustering method to obtain the potential outliers. Then multiple-case diagnostics are used to obtain the outliers from these potential outliers. The performance of this procedure is also compared to Serbert's method. Monte Carlo simulations are used in determining which procedure performed best in all of the linear regression scenarios Faculty of Science 2003-06 Article PeerReviewed application/pdf en http://eprints.utm.my/1193/1/RobiahAdnan2003_MultipleOutliersDetectionProcedures.pdf Adnan, Robiah and Mohamad, Mohd Nor and Setan, Halim (2003) Multiple outliers detection procedures in linear regression. Matematika, 19 (1). pp. 29-45. ISSN 0127-8274 http://www.fs.utm.my/matematika/content/view/79/31/
spellingShingle TA Engineering (General). Civil engineering (General)
Adnan, Robiah
Mohamad, Mohd Nor
Setan, Halim
Multiple outliers detection procedures in linear regression
title Multiple outliers detection procedures in linear regression
title_full Multiple outliers detection procedures in linear regression
title_fullStr Multiple outliers detection procedures in linear regression
title_full_unstemmed Multiple outliers detection procedures in linear regression
title_short Multiple outliers detection procedures in linear regression
title_sort multiple outliers detection procedures in linear regression
topic TA Engineering (General). Civil engineering (General)
url http://eprints.utm.my/1193/
http://eprints.utm.my/1193/
http://eprints.utm.my/1193/1/RobiahAdnan2003_MultipleOutliersDetectionProcedures.pdf