Outlier detection in a circular regression model using COVRATIO statistic
In this article, we model the relationship between two circular variables using the circular regression models, to be called JS circular regression model, which was proposed by Jammalamadaka and Sarma (1993). The model has many interesting properties and is sensitive enough to detect the occurrence...
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| Format: | Article |
| Language: | en |
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Taylor & Francis
2013
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| Online Access: | http://eprints.um.edu.my/10141/1/Outlier_Detection_in_a_Circular.pdf http://eprints.um.edu.my/10141/ http://www.tandfonline.com/doi/abs/10.1080/03610918.2012.697239#.VE3RZFeXCPU http://dx.doi.org/10.1080/03610918.2012.697239 |
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| author | Mohamed, I. Ibrahim, S. Rambli, A. Hussin, A.G. |
| author_facet | Mohamed, I. Ibrahim, S. Rambli, A. Hussin, A.G. |
| author_sort | Mohamed, I. |
| building | UM Library |
| collection | Institutional Repository |
| content_provider | Universiti Malaya |
| content_source | UM Research Repository |
| continent | Asia |
| country | Malaysia |
| description | In this article, we model the relationship between two circular variables using the circular regression models, to be called JS circular regression model, which was proposed
by Jammalamadaka and Sarma (1993). The model has many interesting properties and is sensitive enough to detect the occurrence of outliers. We focus our attention on the
problem of identifying outliers in this model. In particular, we extend the use of the COVRATIO statistic, which has been successfully used in the linear case for the same purpose, to the JS circular regression model via a row deletion approach. Through simulation studies, the cut-off points for the new procedure are obtained and its power of performance is investigated. It is found that the performance improves when the resulting residuals have small variance and when the sample size gets larger. An example of the application of the procedure is presented using a real dataset. |
| format | Article |
| id | my.um.eprints-10141 |
| institution | Universiti Malaya |
| language | en |
| publishDate | 2013 |
| publisher | Taylor & Francis |
| record_format | eprints |
| spelling | my.um.eprints-101412017-07-03T08:28:20Z http://eprints.um.edu.my/10141/ Outlier detection in a circular regression model using COVRATIO statistic Mohamed, I. Ibrahim, S. Rambli, A. Hussin, A.G. QA Mathematics In this article, we model the relationship between two circular variables using the circular regression models, to be called JS circular regression model, which was proposed by Jammalamadaka and Sarma (1993). The model has many interesting properties and is sensitive enough to detect the occurrence of outliers. We focus our attention on the problem of identifying outliers in this model. In particular, we extend the use of the COVRATIO statistic, which has been successfully used in the linear case for the same purpose, to the JS circular regression model via a row deletion approach. Through simulation studies, the cut-off points for the new procedure are obtained and its power of performance is investigated. It is found that the performance improves when the resulting residuals have small variance and when the sample size gets larger. An example of the application of the procedure is presented using a real dataset. Taylor & Francis 2013 Article PeerReviewed application/pdf en http://eprints.um.edu.my/10141/1/Outlier_Detection_in_a_Circular.pdf Mohamed, I. and Ibrahim, S. and Rambli, A. and Hussin, A.G. (2013) Outlier detection in a circular regression model using COVRATIO statistic. Communications in Statistics - Simulation and Computation, 42 (10). pp. 2272-2280. ISSN 0361-0918, DOI https://doi.org/10.1080/03610918.2012.697239 <https://doi.org/10.1080/03610918.2012.697239>. http://www.tandfonline.com/doi/abs/10.1080/03610918.2012.697239#.VE3RZFeXCPU http://dx.doi.org/10.1080/03610918.2012.697239 |
| spellingShingle | QA Mathematics Mohamed, I. Ibrahim, S. Rambli, A. Hussin, A.G. Outlier detection in a circular regression model using COVRATIO statistic |
| title | Outlier detection in a circular regression model using COVRATIO statistic |
| title_full | Outlier detection in a circular regression model using COVRATIO statistic |
| title_fullStr | Outlier detection in a circular regression model using COVRATIO statistic |
| title_full_unstemmed | Outlier detection in a circular regression model using COVRATIO statistic |
| title_short | Outlier detection in a circular regression model using COVRATIO statistic |
| title_sort | outlier detection in a circular regression model using covratio statistic |
| topic | QA Mathematics |
| url | http://eprints.um.edu.my/10141/1/Outlier_Detection_in_a_Circular.pdf http://eprints.um.edu.my/10141/ http://www.tandfonline.com/doi/abs/10.1080/03610918.2012.697239#.VE3RZFeXCPU http://dx.doi.org/10.1080/03610918.2012.697239 |
| url_provider | http://eprints.um.edu.my/ |