Outlier detection in a circular regression model

Recently, there is strong interest on the subject of outlier problem in circular data. In this paper, we focus on detecting outliers in a circular regression model proposed by Down and Mardia. The basic properties of the model are available including the exact form of covariance matrix of the parame...

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Main Authors:	Adzhar Rambli, Rossita Mohamad Yunus, Ibrahim Mohamed, Abdul Ghapor Hussin
Format:	Article
Language:	English
Published:	Universiti Kebangsaan Malaysia 2015
Online Access:	http://journalarticle.ukm.my/8988/ http://journalarticle.ukm.my/8988/ http://journalarticle.ukm.my/8988/1/15_Adzhar_Rambli.pdf

id	ukm-8988
recordtype	eprints
spelling	ukm-89882016-12-14T06:48:38Z http://journalarticle.ukm.my/8988/ Outlier detection in a circular regression model Adzhar Rambli, Rossita Mohamad Yunus, Ibrahim Mohamed, Abdul Ghapor Hussin, Recently, there is strong interest on the subject of outlier problem in circular data. In this paper, we focus on detecting outliers in a circular regression model proposed by Down and Mardia. The basic properties of the model are available including the exact form of covariance matrix of the parameters. Hence, we intend to identify outliers in the model by looking at the effect of the outliers on the covariance matrix. The method resembles closely the COVRATIO statistic for the case of linear regression problem. The corresponding critical values and the performance of the outlier detection procedure are studied via simulations. For illustration, we apply the procedure on the wind data set. Universiti Kebangsaan Malaysia 2015-07 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/8988/1/15_Adzhar_Rambli.pdf Adzhar Rambli, and Rossita Mohamad Yunus, and Ibrahim Mohamed, and Abdul Ghapor Hussin, (2015) Outlier detection in a circular regression model. Sains Malaysiana, 44 (7). pp. 1027-1032. ISSN 0126-6039 http://www.ukm.my/jsm/malay_journals/jilid44bil7_2015/KandunganJilid44Bil7_2015.html
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
language	English
description	Recently, there is strong interest on the subject of outlier problem in circular data. In this paper, we focus on detecting outliers in a circular regression model proposed by Down and Mardia. The basic properties of the model are available including the exact form of covariance matrix of the parameters. Hence, we intend to identify outliers in the model by looking at the effect of the outliers on the covariance matrix. The method resembles closely the COVRATIO statistic for the case of linear regression problem. The corresponding critical values and the performance of the outlier detection procedure are studied via simulations. For illustration, we apply the procedure on the wind data set.
format	Article
author	Adzhar Rambli, Rossita Mohamad Yunus, Ibrahim Mohamed, Abdul Ghapor Hussin,
spellingShingle	Adzhar Rambli, Rossita Mohamad Yunus, Ibrahim Mohamed, Abdul Ghapor Hussin, Outlier detection in a circular regression model
author_facet	Adzhar Rambli, Rossita Mohamad Yunus, Ibrahim Mohamed, Abdul Ghapor Hussin,
author_sort	Adzhar Rambli,
title	Outlier detection in a circular regression model
title_short	Outlier detection in a circular regression model
title_full	Outlier detection in a circular regression model
title_fullStr	Outlier detection in a circular regression model
title_full_unstemmed	Outlier detection in a circular regression model
title_sort	outlier detection in a circular regression model
publisher	Universiti Kebangsaan Malaysia
publishDate	2015
url	http://journalarticle.ukm.my/8988/ http://journalarticle.ukm.my/8988/ http://journalarticle.ukm.my/8988/1/15_Adzhar_Rambli.pdf
first_indexed	2023-09-18T19:53:42Z
last_indexed	2023-09-18T19:53:42Z
_version_	1777406388405796864

Outlier detection in a circular regression model

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