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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Main Authors:	Nurul Hidayah Sadikon, Adriana Irawati Nur Ibrahim, Ibrahim Mohamed, Dharini Pathmanathan
Format:	Article
Language:	English
Published:	Penerbit Universiti Kebangsaan Malaysia 2018
Online Access:	http://journalarticle.ukm.my/12138/ http://journalarticle.ukm.my/12138/ http://journalarticle.ukm.my/12138/1/29%20Nurul%20Hidayah%20Sadikon.pdf

id	ukm-12138
recordtype	eprints
spelling	ukm-121382018-09-28T22:44:23Z http://journalarticle.ukm.my/12138/ A new discordancy test on a regression for cylindrical data Nurul Hidayah Sadikon, Adriana Irawati Nur Ibrahim, Ibrahim Mohamed, Dharini Pathmanathan, 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 2018-06 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/12138/1/29%20Nurul%20Hidayah%20Sadikon.pdf Nurul Hidayah Sadikon, and Adriana Irawati Nur Ibrahim, and Ibrahim Mohamed, and Dharini Pathmanathan, (2018) A new discordancy test on a regression for cylindrical data. Sains Malaysiana, 47 (6). pp. 1319-1326. ISSN 0126-6039 http://www.ukm.my/jsm/english_journals/vol47num6_2018/contentsVol47num6_2018.html
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
language	English
description	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.
format	Article
author	Nurul Hidayah Sadikon, Adriana Irawati Nur Ibrahim, Ibrahim Mohamed, Dharini Pathmanathan,
spellingShingle	Nurul Hidayah Sadikon, Adriana Irawati Nur Ibrahim, Ibrahim Mohamed, Dharini Pathmanathan, A new discordancy test on a regression for cylindrical data
author_facet	Nurul Hidayah Sadikon, Adriana Irawati Nur Ibrahim, Ibrahim Mohamed, Dharini Pathmanathan,
author_sort	Nurul Hidayah Sadikon,
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://journalarticle.ukm.my/12138/ http://journalarticle.ukm.my/12138/ http://journalarticle.ukm.my/12138/1/29%20Nurul%20Hidayah%20Sadikon.pdf
first_indexed	2023-09-18T20:01:56Z
last_indexed	2023-09-18T20:01:56Z
_version_	1777406906950746112

A new discordancy test on a regression for cylindrical data

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