A New Discordancy Test on a Regression for Cylindrical Data
A cylindrical data set consists of circular and linear variables. We focus on developing an outlier detection procedure for cylindrical regression model proposed by Johnson and Wehrly (1978) based on the k-nearest neighbour approach. The procedure is applied based on the residuals where the distance...
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my.um.eprints.208382019-04-08T07:44:54Z http://eprints.um.edu.my/20838/ A New Discordancy Test on a Regression for Cylindrical Data Sadikon, Nurul Hidayah Ibrahim, Adriana Irawati Nur Mohamed, Ibrahim Pathmanathan, Dharini Q Science (General) QA Mathematics A cylindrical data set consists of circular and linear variables. We focus on developing an outlier detection procedure for cylindrical regression model proposed by Johnson and Wehrly (1978) based on the k-nearest neighbour approach. The procedure is applied based on the residuals where the distance between two residuals is measured by the Euclidean distance. This procedure can be used to detect single or multiple outliers. Cut-off points of the test statistic are generated and its performance is then evaluated via simulation. For illustration, we apply the test on the wind data set obtained from the Malaysian Meteorological Department. Penerbit Universiti Kebangsaan Malaysia 2018 Article PeerReviewed Sadikon, Nurul Hidayah and Ibrahim, Adriana Irawati Nur and Mohamed, Ibrahim and Pathmanathan, Dharini (2018) A New Discordancy Test on a Regression for Cylindrical Data. Sains Malaysiana, 47 (6). pp. 1319-1326. ISSN 0126-6039 https://doi.org/10.17576/jsm-2018-4706-29 doi:10.17576/jsm-2018-4706-29 |
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A cylindrical data set consists of circular and linear variables. We focus on developing an outlier detection procedure for cylindrical regression model proposed by Johnson and Wehrly (1978) based on the k-nearest neighbour approach. The procedure is applied based on the residuals where the distance between two residuals is measured by the Euclidean distance. This procedure can be used to detect single or multiple outliers. Cut-off points of the test statistic are generated and its performance is then evaluated via simulation. For illustration, we apply the test on the wind data set obtained from the Malaysian Meteorological Department. |
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Article |
author |
Sadikon, Nurul Hidayah Ibrahim, Adriana Irawati Nur Mohamed, Ibrahim Pathmanathan, Dharini |
author_facet |
Sadikon, Nurul Hidayah Ibrahim, Adriana Irawati Nur Mohamed, Ibrahim Pathmanathan, Dharini |
author_sort |
Sadikon, Nurul Hidayah |
title |
A New Discordancy Test on a Regression for Cylindrical Data |
title_short |
A New Discordancy Test on a Regression for Cylindrical Data |
title_full |
A New Discordancy Test on a Regression for Cylindrical Data |
title_fullStr |
A New Discordancy Test on a Regression for Cylindrical Data |
title_full_unstemmed |
A New Discordancy Test on a Regression for Cylindrical Data |
title_sort |
new discordancy test on a regression for cylindrical data |
publisher |
Penerbit Universiti Kebangsaan Malaysia |
publishDate |
2018 |
url |
http://eprints.um.edu.my/20838/ https://doi.org/10.17576/jsm-2018-4706-29 |
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1643691395328770048 |
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13.160551 |