File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Local likelihood with time-varying additive hazards model

TitleLocal likelihood with time-varying additive hazards model
Authors
KeywordsAdditive model
Asymptotic normality
Censored data
Local polynomial
Maximum likelihood
Nonparametric estimation
Issue Date2007
PublisherStatistical Society of Canada. The Journal's web site is located at http://www.mat.ulaval.ca/cjs
Citation
Canadian Journal Of Statistics, 2007, v. 35 n. 2, p. 321-337 How to Cite?
AbstractThe authors propose the local likelihood method for the time-varying coefficient additive hazards model. They use the Newton-Raphson algorithm to maximize the likelihood into which a local polynomial expansion has been incorporated. They establish the asymptotic properties for the time-varying coefficient estimators and derive explicit expressions for the variance and bias. The authors present simulation results describing the performance of their approach for finite sample sizes. Their numerical comparisons show the stability and efficiency of the local maximum likelihood estimator. They finally illustrate their proposal with data from a laryngeal cancer clinical study.
Persistent Identifierhttp://hdl.handle.net/10722/146582
ISSN
2015 Impact Factor: 0.413
2015 SCImago Journal Rankings: 0.737
References

 

DC FieldValueLanguage
dc.contributor.authorLi, Hen_HK
dc.contributor.authorYin, Gen_HK
dc.contributor.authorZhou, Yen_HK
dc.date.accessioned2012-05-02T08:37:11Z-
dc.date.available2012-05-02T08:37:11Z-
dc.date.issued2007en_HK
dc.identifier.citationCanadian Journal Of Statistics, 2007, v. 35 n. 2, p. 321-337en_HK
dc.identifier.issn0319-5724en_HK
dc.identifier.urihttp://hdl.handle.net/10722/146582-
dc.description.abstractThe authors propose the local likelihood method for the time-varying coefficient additive hazards model. They use the Newton-Raphson algorithm to maximize the likelihood into which a local polynomial expansion has been incorporated. They establish the asymptotic properties for the time-varying coefficient estimators and derive explicit expressions for the variance and bias. The authors present simulation results describing the performance of their approach for finite sample sizes. Their numerical comparisons show the stability and efficiency of the local maximum likelihood estimator. They finally illustrate their proposal with data from a laryngeal cancer clinical study.en_HK
dc.languageengen_US
dc.publisherStatistical Society of Canada. The Journal's web site is located at http://www.mat.ulaval.ca/cjsen_HK
dc.relation.ispartofCanadian Journal of Statisticsen_HK
dc.subjectAdditive modelen_HK
dc.subjectAsymptotic normalityen_HK
dc.subjectCensored dataen_HK
dc.subjectLocal polynomialen_HK
dc.subjectMaximum likelihooden_HK
dc.subjectNonparametric estimationen_HK
dc.titleLocal likelihood with time-varying additive hazards modelen_HK
dc.typeArticleen_HK
dc.identifier.emailYin, G: gyin@hku.hken_HK
dc.identifier.authorityYin, G=rp00831en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-34447644807en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-34447644807&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume35en_HK
dc.identifier.issue2en_HK
dc.identifier.spage321en_HK
dc.identifier.epage337en_HK
dc.publisher.placeCanadaen_HK
dc.identifier.scopusauthoridLi, H=8423900800en_HK
dc.identifier.scopusauthoridYin, G=8725807500en_HK
dc.identifier.scopusauthoridZhou, Y=10140084400en_HK

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats