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Adjusting outliers in univariate circular data


Citation

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

Abstract / Synopsis

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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Additional Metadata

Item Type: Article
Divisions: Faculty of Science
Institute for Mathematical Research
Publisher: Universiti Putra Malaysia Press
Keywords: Directional data; Circular data; Circular mean; Circular distance; Outlier
Depositing User: Nabilah Mustapa
Date Deposited: 10 Jan 2018 13:31
Last Modified: 25 Jan 2018 16:55
URI: http://psasir.upm.edu.my/id/eprint/58323
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