Mohamed, I. and Abuzaid, A.H. and Hussin, A.G. (2013) Detection of outliers in simple circular regression models using the mean circular error statistic. Journal of Statistical Computation and Simulation, 83 (2). pp. 269-277. ISSN 0094-9655,
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Abstract
The investigation on the identification of outliers in linear regression models can be extended to those for circular regression case. In this paper, we propose a new numerical statistic called mean circular error to identify possible outliers in circular regression models by using a row deletion approach. Through intensive simulation studies, the cut-off points of the statistic are obtained and its power of performance investigated.It is found that the performance improves as the concentration parameter of circular residuals becomes larger or the sample size becomes smaller. As an illustration, the statistic is applied to a wind direction data set.
Item Type: | Article |
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Funders: | UNSPECIFIED |
Additional Information: | Institute of Mathematical Sciences, University of Malaya |
Uncontrolled Keywords: | Circular distance; circular regression model; mean circular error; outlier; row deletion |
Subjects: | Q Science > QA Mathematics |
Divisions: | Faculty of Science > Institute of Mathematical Sciences |
Depositing User: | Ms. Izzan Ramizah Idris |
Date Deposited: | 13 Nov 2014 04:12 |
Last Modified: | 13 Nov 2014 04:12 |
URI: | http://eprints.um.edu.my/id/eprint/10160 |
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