Robust trimmed mean direction to estimate circular location parameter in the presence of outliers
Mean direction is a good measure to estimate circular location parameter in univariate circular data. However, it is bias and cause misleading when the circular data has some outliers, especially with increasing ratio of outliers. Trimmed mean is one of robust method to estimate location parameter....
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Medwell Publishing
2018
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Online Access: | http://psasir.upm.edu.my/id/eprint/73816/1/Robust%20trimmed%20mean%20direction%20to%20estimate%20circular%20location%20parameter%20in%20the%20presence%20of%20outliers.pdf http://psasir.upm.edu.my/id/eprint/73816/ https://medwelljournals.com/abstract/?doi=jeasci.2018.6612.6615 |
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my.upm.eprints.738162020-05-06T18:05:22Z http://psasir.upm.edu.my/id/eprint/73816/ Robust trimmed mean direction to estimate circular location parameter in the presence of outliers Midi, Habshah Mahmood, Ehab A. Hussin, Abdul Ghapor Arasan, Jayanthi Mean direction is a good measure to estimate circular location parameter in univariate circular data. However, it is bias and cause misleading when the circular data has some outliers, especially with increasing ratio of outliers. Trimmed mean is one of robust method to estimate location parameter. Therefore in this study, it is focused to find a robust formula for trimming the circular data. This proposed method is compared with mean direction, median direction and M estimator for clean and contaminated data. Results of simulation study and real data prove that trimmed mean direction is very successful and the best among them. Medwell Publishing 2018 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/73816/1/Robust%20trimmed%20mean%20direction%20to%20estimate%20circular%20location%20parameter%20in%20the%20presence%20of%20outliers.pdf Midi, Habshah and Mahmood, Ehab A. and Hussin, Abdul Ghapor and Arasan, Jayanthi (2018) Robust trimmed mean direction to estimate circular location parameter in the presence of outliers. Journal of Engineering and Applied Sciences, 13 (16). 6612 - 6615. ISSN 1818-7803; ESSN: 1816-949X https://medwelljournals.com/abstract/?doi=jeasci.2018.6612.6615 10.36478/jeasci.2018.6612.6615 |
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Mean direction is a good measure to estimate circular location parameter in univariate circular data. However, it is bias and cause misleading when the circular data has some outliers, especially with increasing ratio of outliers. Trimmed mean is one of robust method to estimate location parameter. Therefore in this study, it is focused to find a robust formula for trimming the circular data. This proposed method is compared with mean direction, median direction and M estimator for clean and contaminated data. Results of simulation study and real data prove that trimmed mean direction is very successful and the best among them. |
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Article |
author |
Midi, Habshah Mahmood, Ehab A. Hussin, Abdul Ghapor Arasan, Jayanthi |
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Midi, Habshah Mahmood, Ehab A. Hussin, Abdul Ghapor Arasan, Jayanthi Robust trimmed mean direction to estimate circular location parameter in the presence of outliers |
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Midi, Habshah Mahmood, Ehab A. Hussin, Abdul Ghapor Arasan, Jayanthi |
author_sort |
Midi, Habshah |
title |
Robust trimmed mean direction to estimate circular location parameter in the presence of outliers |
title_short |
Robust trimmed mean direction to estimate circular location parameter in the presence of outliers |
title_full |
Robust trimmed mean direction to estimate circular location parameter in the presence of outliers |
title_fullStr |
Robust trimmed mean direction to estimate circular location parameter in the presence of outliers |
title_full_unstemmed |
Robust trimmed mean direction to estimate circular location parameter in the presence of outliers |
title_sort |
robust trimmed mean direction to estimate circular location parameter in the presence of outliers |
publisher |
Medwell Publishing |
publishDate |
2018 |
url |
http://psasir.upm.edu.my/id/eprint/73816/1/Robust%20trimmed%20mean%20direction%20to%20estimate%20circular%20location%20parameter%20in%20the%20presence%20of%20outliers.pdf http://psasir.upm.edu.my/id/eprint/73816/ https://medwelljournals.com/abstract/?doi=jeasci.2018.6612.6615 |
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