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Standard errors estimation in the presence of high leverage point and heteroscedastic errors in multiple linear regression

In this study, the Robust Heteroscedastic Consistent Covariance Matrix (RHCCM) was proposed in order to estimate standard errors of regression coefficients in the presence of high leverage points and heteroscedastic errors in multiple linear regression. Robust Heteroscedastic Consistent Covariance M...

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Main Authors: Khoo, Li Peng, Adnan, Robiah, Ahmad, Maizah Hura
Format: Conference or Workshop Item
Published: 2013
Subjects:
Q Science
Online Access:http://eprints.utm.my/id/eprint/38580/
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spelling my.utm.385802017-09-26T03:47:42Z http://eprints.utm.my/id/eprint/38580/ Standard errors estimation in the presence of high leverage point and heteroscedastic errors in multiple linear regression Khoo, Li Peng Adnan, Robiah Ahmad, Maizah Hura Q Science In this study, the Robust Heteroscedastic Consistent Covariance Matrix (RHCCM) was proposed in order to estimate standard errors of regression coefficients in the presence of high leverage points and heteroscedastic errors in multiple linear regression. Robust Heteroscedastic Consistent Covariance Matrix (RHCCM) is the combination of a robust method and Heteroscedasticit Consistent Covariance Matrix (HCCM). The robust method is used to eliminate the effect of high leverage points while HCCM is mainly used to eliminate the effect of heteroscedastic errors. The performance of RHCCM was assessed through an empirical study and compared with results obtained when the original Heteroscedastic Consistent Covariance Matrix was used. 2013 Conference or Workshop Item PeerReviewed Khoo, Li Peng and Adnan, Robiah and Ahmad, Maizah Hura (2013) Standard errors estimation in the presence of high leverage point and heteroscedastic errors in multiple linear regression. In: (ICOWOBAS - RAFSS 2013) 4th International Conference & Workshop on Basic & Applied Science, 2013.
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic Q Science
spellingShingle Q Science
Khoo, Li Peng
Adnan, Robiah
Ahmad, Maizah Hura
Standard errors estimation in the presence of high leverage point and heteroscedastic errors in multiple linear regression
description In this study, the Robust Heteroscedastic Consistent Covariance Matrix (RHCCM) was proposed in order to estimate standard errors of regression coefficients in the presence of high leverage points and heteroscedastic errors in multiple linear regression. Robust Heteroscedastic Consistent Covariance Matrix (RHCCM) is the combination of a robust method and Heteroscedasticit Consistent Covariance Matrix (HCCM). The robust method is used to eliminate the effect of high leverage points while HCCM is mainly used to eliminate the effect of heteroscedastic errors. The performance of RHCCM was assessed through an empirical study and compared with results obtained when the original Heteroscedastic Consistent Covariance Matrix was used.
format Conference or Workshop Item
author Khoo, Li Peng
Adnan, Robiah
Ahmad, Maizah Hura
author_facet Khoo, Li Peng
Adnan, Robiah
Ahmad, Maizah Hura
author_sort Khoo, Li Peng
title Standard errors estimation in the presence of high leverage point and heteroscedastic errors in multiple linear regression
title_short Standard errors estimation in the presence of high leverage point and heteroscedastic errors in multiple linear regression
title_full Standard errors estimation in the presence of high leverage point and heteroscedastic errors in multiple linear regression
title_fullStr Standard errors estimation in the presence of high leverage point and heteroscedastic errors in multiple linear regression
title_full_unstemmed Standard errors estimation in the presence of high leverage point and heteroscedastic errors in multiple linear regression
title_sort standard errors estimation in the presence of high leverage point and heteroscedastic errors in multiple linear regression
publishDate 2013
url http://eprints.utm.my/id/eprint/38580/
_version_ 1643650259555975168
score 13.251813

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