Robust autocorrelation testing in multiple linear regression

It is very essential to detect the autocorrelation problem due to its responsibility for ruining the important properties of Ordinary Least Squares (OLS) estimates. The Breusch-Godfrey test is the most commonly used method for autocorrelation detection. However, not many statistics practitioners awa...

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Main Authors: Ann L.H., Midi H.
Other Authors: 55015943700
Format: Article
Published: 2023
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spelling my.uniten.dspace-294932023-12-28T14:30:15Z Robust autocorrelation testing in multiple linear regression Ann L.H. Midi H. 55015943700 6506172362 Autocorrelation High Leverage Points Robust Breusch-Godfrey Test It is very essential to detect the autocorrelation problem due to its responsibility for ruining the important properties of Ordinary Least Squares (OLS) estimates. The Breusch-Godfrey test is the most commonly used method for autocorrelation detection. However, not many statistics practitioners aware that this test is easily affected by high leverage points. In this paper, we proposed a new robust Breusch-Godfrey test which is resistant to the high leverage points. The results of the study signify that the robustified Breusch-Godfrey test is very powerful in the detection of autocorrelation problem with and without the presence of high leverage points. Final 2023-12-28T06:30:15Z 2023-12-28T06:30:15Z 2012 Article 2-s2.0-84857287884 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84857287884&partnerID=40&md5=893c948b95fd6a020b97bff347743bbc https://irepository.uniten.edu.my/handle/123456789/29493 6 1 119 126 Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Autocorrelation
High Leverage Points
Robust Breusch-Godfrey Test
spellingShingle Autocorrelation
High Leverage Points
Robust Breusch-Godfrey Test
Ann L.H.
Midi H.
Robust autocorrelation testing in multiple linear regression
description It is very essential to detect the autocorrelation problem due to its responsibility for ruining the important properties of Ordinary Least Squares (OLS) estimates. The Breusch-Godfrey test is the most commonly used method for autocorrelation detection. However, not many statistics practitioners aware that this test is easily affected by high leverage points. In this paper, we proposed a new robust Breusch-Godfrey test which is resistant to the high leverage points. The results of the study signify that the robustified Breusch-Godfrey test is very powerful in the detection of autocorrelation problem with and without the presence of high leverage points.
author2 55015943700
author_facet 55015943700
Ann L.H.
Midi H.
format Article
author Ann L.H.
Midi H.
author_sort Ann L.H.
title Robust autocorrelation testing in multiple linear regression
title_short Robust autocorrelation testing in multiple linear regression
title_full Robust autocorrelation testing in multiple linear regression
title_fullStr Robust autocorrelation testing in multiple linear regression
title_full_unstemmed Robust autocorrelation testing in multiple linear regression
title_sort robust autocorrelation testing in multiple linear regression
publishDate 2023
_version_ 1806424503864000512
score 13.214268