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Robust autocorrelation testing in multiple linear regression

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dc.citedby3
dc.contributor.authorAnn L.H.en_US
dc.contributor.authorMidi H.en_US
dc.contributor.authorid55015943700en_US
dc.contributor.authorid6506172362en_US
dc.date.accessioned2023-12-28T06:30:15Z
dc.date.available2023-12-28T06:30:15Z
dc.date.issued2012
dc.description.abstractIt 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.en_US
dc.description.natureFinalen_US
dc.identifier.epage126
dc.identifier.issue1
dc.identifier.scopus2-s2.0-84857287884
dc.identifier.spage119
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84857287884&partnerID=40&md5=893c948b95fd6a020b97bff347743bbc
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/29493
dc.identifier.volume6
dc.pagecount7
dc.sourceScopus
dc.sourcetitleInternational Journal of Mathematics and Computers in Simulation
dc.subjectAutocorrelation
dc.subjectHigh Leverage Points
dc.subjectRobust Breusch-Godfrey Test
dc.titleRobust autocorrelation testing in multiple linear regressionen_US
dc.typeArticleen_US
dspace.entity.typePublication
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