Adjusting outliers in univariate circular data

Circular data analysis is a particular branch of statistics that sits somewhere between the analysis of linear data and the analysis of spherical data. Circular data are used in many scientific fields. The efficiency of the statistical methods that are applied depends on the accuracy of the data in...

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Main Authors: Mahmood, Ehab A., Rana, Md. Sohel, Hussin, Abdul Ghapor, Midi, Habshah
Format: Article
Language:English
Published: Universiti Putra Malaysia Press 2017
Online Access:http://psasir.upm.edu.my/id/eprint/58323/1/08%20JST-0626-2016-2ndProof.pdf
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author Mahmood, Ehab A.
Rana, Md. Sohel
Hussin, Abdul Ghapor
Midi, Habshah
author_facet Mahmood, Ehab A.
Rana, Md. Sohel
Hussin, Abdul Ghapor
Midi, Habshah
author_sort Mahmood, Ehab A.
collection UPM
description Circular data analysis is a particular branch of statistics that sits somewhere between the analysis of linear data and the analysis of spherical data. Circular data are used in many scientific fields. The efficiency of the statistical methods that are applied depends on the accuracy of the data in the study. However, circular data may have outliers that cannot be deleted. If this is the case, we have two ways to avoid the effect of outliers. First, we can apply robust methods for statistical estimations. Second, we can adjust the outliers using the other clean data points in the dataset. In this paper, we focus on adjusting outliers in circular data using the circular distance between the circular data points and the circular mean direction. The proposed procedure is tested by applying it to a simulation study and to real data sets. The results show that the proposed procedure can adjust outliers according to the measures used in the paper.
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spelling upm.eprints-583232018-01-25T08:55:08Z http://psasir.upm.edu.my/id/eprint/58323/ Adjusting outliers in univariate circular data Mahmood, Ehab A. Rana, Md. Sohel Hussin, Abdul Ghapor Midi, Habshah Circular data analysis is a particular branch of statistics that sits somewhere between the analysis of linear data and the analysis of spherical data. Circular data are used in many scientific fields. The efficiency of the statistical methods that are applied depends on the accuracy of the data in the study. However, circular data may have outliers that cannot be deleted. If this is the case, we have two ways to avoid the effect of outliers. First, we can apply robust methods for statistical estimations. Second, we can adjust the outliers using the other clean data points in the dataset. In this paper, we focus on adjusting outliers in circular data using the circular distance between the circular data points and the circular mean direction. The proposed procedure is tested by applying it to a simulation study and to real data sets. The results show that the proposed procedure can adjust outliers according to the measures used in the paper. Universiti Putra Malaysia Press 2017 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/58323/1/08%20JST-0626-2016-2ndProof.pdf Mahmood, Ehab A. and Rana, Md. Sohel and Hussin, Abdul Ghapor and Midi, Habshah (2017) Adjusting outliers in univariate circular data. Pertanika Journal of Science & Technology, 25 (4). pp. 1147-1158. ISSN 0128-7680; ESSN: 2231-8526 http://www.pertanika.upm.edu.my/Pertanika%20PAPERS/JST%20Vol.%2025%20(4)%20Oct.%202017/08%20JST-0626-2016-2ndProof.pdf
spellingShingle Mahmood, Ehab A.
Rana, Md. Sohel
Hussin, Abdul Ghapor
Midi, Habshah
Adjusting outliers in univariate circular data
title Adjusting outliers in univariate circular data
title_full Adjusting outliers in univariate circular data
title_fullStr Adjusting outliers in univariate circular data
title_full_unstemmed Adjusting outliers in univariate circular data
title_short Adjusting outliers in univariate circular data
title_sort adjusting outliers in univariate circular data
url http://psasir.upm.edu.my/id/eprint/58323/1/08%20JST-0626-2016-2ndProof.pdf
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