A comparison between classical and robust method in a factorial design in the presence of outlier
Analysis of Variance (ANOVA) techniques which is based on classical Least Squares (LS) method requires several assumptions, such as normality, constant variances and independency. Those assumptions can be violated due to several causes, such as the presence of an outlying observation. There are m...
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Science Publications
2013
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my.upm.eprints.303152015-09-18T07:35:16Z http://psasir.upm.edu.my/id/eprint/30315/ A comparison between classical and robust method in a factorial design in the presence of outlier Fitrianto, Anwar Midi, Habshah Analysis of Variance (ANOVA) techniques which is based on classical Least Squares (LS) method requires several assumptions, such as normality, constant variances and independency. Those assumptions can be violated due to several causes, such as the presence of an outlying observation. There are many evident in literatures that the LS estimate is easily affected by outliers. To remedy this problem, a robust procedure that provides estimation, inference and testing that are not influenced by outlying observations is put forward. A well-known approach to handle dataset with outliers is the M-estimation. In this study, both classical and robust procedures are employed to data of a factorial experiment. The results signify that the classical method of least squares estimates instead of robust methods lead to misleading conclusion of the analysis in factorial designs. Science Publications 2013 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/30315/1/A%20comparison%20between%20classical%20and%20robust%20method%20in%20a%20factorial%20design%20in%20the%20presence%20of%20outlier.pdf Fitrianto, Anwar and Midi, Habshah (2013) A comparison between classical and robust method in a factorial design in the presence of outlier. Journal of Mathematics and Statistics, 9 (3). pp. 193-197. ISSN 1549-3644 10.3844/jmssp.2013.193.197 English |
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Analysis of Variance (ANOVA) techniques which is based on classical Least Squares (LS) method requires
several assumptions, such as normality, constant variances and independency. Those assumptions can be
violated due to several causes, such as the presence of an outlying observation. There are many evident in
literatures that the LS estimate is easily affected by outliers. To remedy this problem, a robust procedure
that provides estimation, inference and testing that are not influenced by outlying observations is put
forward. A well-known approach to handle dataset with outliers is the M-estimation. In this study, both
classical and robust procedures are employed to data of a factorial experiment. The results signify that the
classical method of least squares estimates instead of robust methods lead to misleading conclusion of the
analysis in factorial designs. |
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Article |
author |
Fitrianto, Anwar Midi, Habshah |
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Fitrianto, Anwar Midi, Habshah A comparison between classical and robust method in a factorial design in the presence of outlier |
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Fitrianto, Anwar Midi, Habshah |
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Fitrianto, Anwar |
title |
A comparison between classical and robust method in a factorial design in the presence of outlier |
title_short |
A comparison between classical and robust method in a factorial design in the presence of outlier |
title_full |
A comparison between classical and robust method in a factorial design in the presence of outlier |
title_fullStr |
A comparison between classical and robust method in a factorial design in the presence of outlier |
title_full_unstemmed |
A comparison between classical and robust method in a factorial design in the presence of outlier |
title_sort |
comparison between classical and robust method in a factorial design in the presence of outlier |
publisher |
Science Publications |
publishDate |
2013 |
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http://psasir.upm.edu.my/id/eprint/30315/1/A%20comparison%20between%20classical%20and%20robust%20method%20in%20a%20factorial%20design%20in%20the%20presence%20of%20outlier.pdf http://psasir.upm.edu.my/id/eprint/30315/ |
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