Detection of outliers in simple circular regression models using the mean circular error statistic

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 ap...

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Main Authors: Mohamed, I., Abuzaid, A.H., Hussin, A.G.
Format: Article
Language:English
Published: Taylor & Francis 2013
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Online Access:http://eprints.um.edu.my/10160/1/Detection_of_outliers_in_simple_circular_regression_models_using.pdf
http://eprints.um.edu.my/10160/
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spelling my.um.eprints.101602014-11-13T04:12:33Z http://eprints.um.edu.my/10160/ Detection of outliers in simple circular regression models using the mean circular error statistic Mohamed, I. Abuzaid, A.H. Hussin, A.G. QA Mathematics 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. Taylor & Francis 2013 Article PeerReviewed application/pdf en http://eprints.um.edu.my/10160/1/Detection_of_outliers_in_simple_circular_regression_models_using.pdf 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
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Mohamed, I.
Abuzaid, A.H.
Hussin, A.G.
Detection of outliers in simple circular regression models using the mean circular error statistic
description 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.
format Article
author Mohamed, I.
Abuzaid, A.H.
Hussin, A.G.
author_facet Mohamed, I.
Abuzaid, A.H.
Hussin, A.G.
author_sort Mohamed, I.
title Detection of outliers in simple circular regression models using the mean circular error statistic
title_short Detection of outliers in simple circular regression models using the mean circular error statistic
title_full Detection of outliers in simple circular regression models using the mean circular error statistic
title_fullStr Detection of outliers in simple circular regression models using the mean circular error statistic
title_full_unstemmed Detection of outliers in simple circular regression models using the mean circular error statistic
title_sort detection of outliers in simple circular regression models using the mean circular error statistic
publisher Taylor & Francis
publishDate 2013
url http://eprints.um.edu.my/10160/1/Detection_of_outliers_in_simple_circular_regression_models_using.pdf
http://eprints.um.edu.my/10160/
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score 13.160551