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Article: The mean-shift outlier model in general weighted regression and its applications

TitleThe mean-shift outlier model in general weighted regression and its applications
Authors
KeywordsGeneralized Estimating Equations
Influential Observations
One-Step Approximation
Regression Diagnostics
Issue Date1999
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/csda
Citation
Computational Statistics And Data Analysis, 1999, v. 30 n. 4, p. 429-441 How to Cite?
AbstractConsider the general weighted linear regression model y=Xβ+ε, where E(ε)=0,Cov(ε)=Vσ 2,σ 2 is an unknown positive scalar, and V is a symmetric positive-definite matrix not necessary diagonal. Two models, the mean-shift outlier model and the case-deletion model, can be employed to develop multiple case-deletion diagnostics for the linear model. The multiple case-deletion diagnostics are obtained via the mean-shift outlier model in this article and are shown to be equivalent to the deletion diagnostics via the case deletion model obtained by Preisser and Qaqish (1996, Biometrika, 83, 551-562). In addition, computing the multiple case-deletion diagnostics obtained via the mean-shift outlier model is faster than computing the one based on the more commonly used case-deletion model in some situations. Applications of the multiple deletion diagnostics developed from the mean-shift outlier model are also given for regression analysis with the likelihood function available and regression analysis based on generalized estimating equations. These applications include survival models and the generalized estimating equations of Liang and Zeger (1986, Biometrika, 73, 13-22). Several numerical experiments as well as a real example are given as illustrations. © 1999 Elsevier Science B.V.
Persistent Identifierhttp://hdl.handle.net/10722/172381
ISSN
2015 Impact Factor: 1.179
2015 SCImago Journal Rankings: 1.283
References

 

DC FieldValueLanguage
dc.contributor.authorWei, WHen_US
dc.contributor.authorFung, WKen_US
dc.date.accessioned2012-10-30T06:22:14Z-
dc.date.available2012-10-30T06:22:14Z-
dc.date.issued1999en_US
dc.identifier.citationComputational Statistics And Data Analysis, 1999, v. 30 n. 4, p. 429-441en_US
dc.identifier.issn0167-9473en_US
dc.identifier.urihttp://hdl.handle.net/10722/172381-
dc.description.abstractConsider the general weighted linear regression model y=Xβ+ε, where E(ε)=0,Cov(ε)=Vσ 2,σ 2 is an unknown positive scalar, and V is a symmetric positive-definite matrix not necessary diagonal. Two models, the mean-shift outlier model and the case-deletion model, can be employed to develop multiple case-deletion diagnostics for the linear model. The multiple case-deletion diagnostics are obtained via the mean-shift outlier model in this article and are shown to be equivalent to the deletion diagnostics via the case deletion model obtained by Preisser and Qaqish (1996, Biometrika, 83, 551-562). In addition, computing the multiple case-deletion diagnostics obtained via the mean-shift outlier model is faster than computing the one based on the more commonly used case-deletion model in some situations. Applications of the multiple deletion diagnostics developed from the mean-shift outlier model are also given for regression analysis with the likelihood function available and regression analysis based on generalized estimating equations. These applications include survival models and the generalized estimating equations of Liang and Zeger (1986, Biometrika, 73, 13-22). Several numerical experiments as well as a real example are given as illustrations. © 1999 Elsevier Science B.V.en_US
dc.languageengen_US
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/csdaen_US
dc.relation.ispartofComputational Statistics and Data Analysisen_US
dc.subjectGeneralized Estimating Equationsen_US
dc.subjectInfluential Observationsen_US
dc.subjectOne-Step Approximationen_US
dc.subjectRegression Diagnosticsen_US
dc.titleThe mean-shift outlier model in general weighted regression and its applicationsen_US
dc.typeArticleen_US
dc.identifier.emailFung, WK: wingfung@hku.hken_US
dc.identifier.authorityFung, WK=rp00696en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-0032634822en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0032634822&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume30en_US
dc.identifier.issue4en_US
dc.identifier.spage429en_US
dc.identifier.epage441en_US
dc.publisher.placeNetherlandsen_US
dc.identifier.scopusauthoridWei, WH=7403321505en_US
dc.identifier.scopusauthoridFung, WK=13310399400en_US

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