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Article: Local Influence Analysis for Penalized Gaussian Likelihood Estimators in Partially Linear Models

TitleLocal Influence Analysis for Penalized Gaussian Likelihood Estimators in Partially Linear Models
Authors
Zhu, ZYHe, XFung, WK
KeywordsDiagnostics
Local influence
Longitudinal data
Mixed model
Partially linear
Penalized likelihood
Regression
Smoothing spline
Issue Date2003
PublisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/SJOS
Citation
Scandinavian Journal Of Statistics, 2003, v. 30 n. 4, p. 767-780 How to Cite?
AbstractPartially linear models are extensions of linear models to include a non-parametric function of some covariate. They have been found to be useful in both cross-sectional and longitudinal studies. This paper provides a convenient means to extend Cook's local influence analysis to the penalized Gaussian likelihood estimator that uses a smoothing spline as a solution to its non-parametric component. Insight is also provided into the interplay of the influence or leverage measures between the linear and the non-parametric components in the model. The diagnostics are applied to a mouth wash data set and a longitudinal hormone study with informative results.
Persistent Identifierhttp://hdl.handle.net/10722/82989
ISSN
0303-6898
2021 Impact Factor: 1.040
2020 SCImago Journal Rankings: 1.359
References
References in Scopus

 

DC FieldValueLanguage
dc.contributor.authorZhu, ZYen_HK
dc.contributor.authorHe, Xen_HK
dc.contributor.authorFung, WKen_HK
dc.date.accessioned2010-09-06T08:35:40Z-
dc.date.available2010-09-06T08:35:40Z-
dc.date.issued2003en_HK
dc.identifier.citationScandinavian Journal Of Statistics, 2003, v. 30 n. 4, p. 767-780en_HK
dc.identifier.issn0303-6898en_HK
dc.identifier.urihttp://hdl.handle.net/10722/82989-
dc.description.abstractPartially linear models are extensions of linear models to include a non-parametric function of some covariate. They have been found to be useful in both cross-sectional and longitudinal studies. This paper provides a convenient means to extend Cook's local influence analysis to the penalized Gaussian likelihood estimator that uses a smoothing spline as a solution to its non-parametric component. Insight is also provided into the interplay of the influence or leverage measures between the linear and the non-parametric components in the model. The diagnostics are applied to a mouth wash data set and a longitudinal hormone study with informative results.en_HK
dc.languageengen_HK
dc.publisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/SJOSen_HK
dc.relation.ispartofScandinavian Journal of Statisticsen_HK
dc.rightsScandinavian Journal of Statistics. Copyright © Blackwell Publishing Ltd.en_HK
dc.subjectDiagnosticsen_HK
dc.subjectLocal influenceen_HK
dc.subjectLongitudinal dataen_HK
dc.subjectMixed modelen_HK
dc.subjectPartially linearen_HK
dc.subjectPenalized likelihooden_HK
dc.subjectRegressionen_HK
dc.subjectSmoothing splineen_HK
dc.titleLocal Influence Analysis for Penalized Gaussian Likelihood Estimators in Partially Linear Modelsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0303-6898&volume=30&spage=767&epage=780&date=2003&atitle=Local+influence+analysis+for+penalized+Gaussian+likelihood+estimators+in+partially+linear+modelsen_HK
dc.identifier.emailFung, WK: wingfung@hku.hken_HK
dc.identifier.authorityFung, WK=rp00696en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-0242458498en_HK
dc.identifier.hkuros90700en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0242458498&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume30en_HK
dc.identifier.issue4en_HK
dc.identifier.spage767en_HK
dc.identifier.epage780en_HK
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridZhu, ZY=23487505000en_HK
dc.identifier.scopusauthoridHe, X=7404407842en_HK
dc.identifier.scopusauthoridFung, WK=13310399400en_HK
dc.identifier.issnl0303-6898-

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