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Article: Semiparametric median residual life model and inference

TitleSemiparametric median residual life model and inference
Authors
KeywordsIdentifiability
Median regression
Residual lifetime
Semiparametric model
Survival function
Issue Date2010
PublisherStatistical Society of Canada. The Journal's web site is located at http://www.mat.ulaval.ca/cjs
Citation
Canadian Journal Of Statistics, 2010, v. 38 n. 4, p. 665-679 How to Cite?
AbstractFor randomly censored data, the authors propose a general class of semiparametric median residual life models. They incorporate covariates in a generalized linear form while leaving the baseline median residual life function completely unspecified. Despite the non-identifiability of the survival function for a given median residual life function, a simple and natural procedure is proposed to estimate the regression parameters and the baseline median residual life function. The authors derive the asymptotic properties for the estimators, and demonstrate the numerical performance of the proposed method through simulation studies. The median residual life model can be easily generalized to model other quantiles, and the estimation method can also be applied to the mean residual life model. © 2010 Statistical Society of Canada.
Persistent Identifierhttp://hdl.handle.net/10722/129371
ISSN
2015 Impact Factor: 0.413
2015 SCImago Journal Rankings: 0.737
ISI Accession Number ID
Funding AgencyGrant Number
US NSF
Funding Information:

Ma's research was supported by a US NSF grant The authors are grateful to the Associate Editor referee and Paul Gustafson for their critical and insightful comments, which led to great improvements in the revised manuscript

References

 

DC FieldValueLanguage
dc.contributor.authorMa, Yen_HK
dc.contributor.authorYin, Gen_HK
dc.date.accessioned2010-12-23T08:36:23Z-
dc.date.available2010-12-23T08:36:23Z-
dc.date.issued2010en_HK
dc.identifier.citationCanadian Journal Of Statistics, 2010, v. 38 n. 4, p. 665-679en_HK
dc.identifier.issn0319-5724en_HK
dc.identifier.urihttp://hdl.handle.net/10722/129371-
dc.description.abstractFor randomly censored data, the authors propose a general class of semiparametric median residual life models. They incorporate covariates in a generalized linear form while leaving the baseline median residual life function completely unspecified. Despite the non-identifiability of the survival function for a given median residual life function, a simple and natural procedure is proposed to estimate the regression parameters and the baseline median residual life function. The authors derive the asymptotic properties for the estimators, and demonstrate the numerical performance of the proposed method through simulation studies. The median residual life model can be easily generalized to model other quantiles, and the estimation method can also be applied to the mean residual life model. © 2010 Statistical Society of Canada.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.subjectIdentifiabilityen_HK
dc.subjectMedian regressionen_HK
dc.subjectResidual lifetimeen_HK
dc.subjectSemiparametric modelen_HK
dc.subjectSurvival functionen_HK
dc.titleSemiparametric median residual life model and inferenceen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0319-5724&volume=38&issue=4&spage=665&epage=679&date=2010&atitle=Semiparametric+median+residual+life+model+and+inference-
dc.identifier.emailYin, G: gyin@hku.hken_HK
dc.identifier.authorityYin, G=rp00831en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/cjs.10076en_HK
dc.identifier.scopuseid_2-s2.0-78149364862en_HK
dc.identifier.hkuros177204en_US
dc.identifier.hkuros195656-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-78149364862&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume38en_HK
dc.identifier.issue4en_HK
dc.identifier.spage665en_HK
dc.identifier.epage679en_HK
dc.identifier.isiWOS:000284674900009-
dc.publisher.placeCanadaen_HK
dc.identifier.scopusauthoridMa, Y=8908626500en_HK
dc.identifier.scopusauthoridYin, G=8725807500en_HK

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