File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1002/cjs.10076
- Scopus: eid_2-s2.0-78149364862
- WOS: WOS:000284674900009
- Find via
Supplementary
- Citations:
- Appears in Collections:
Article: Semiparametric median residual life model and inference
Title | Semiparametric median residual life model and inference | ||||
---|---|---|---|---|---|
Authors | |||||
Keywords | Identifiability Median regression Residual lifetime Semiparametric model Survival function | ||||
Issue Date | 2010 | ||||
Publisher | Statistical 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? | ||||
Abstract | For 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 Identifier | http://hdl.handle.net/10722/129371 | ||||
ISSN | 2023 Impact Factor: 0.8 2023 SCImago Journal Rankings: 0.508 | ||||
ISI Accession Number ID |
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 Field | Value | Language |
---|---|---|
dc.contributor.author | Ma, Y | en_HK |
dc.contributor.author | Yin, G | en_HK |
dc.date.accessioned | 2010-12-23T08:36:23Z | - |
dc.date.available | 2010-12-23T08:36:23Z | - |
dc.date.issued | 2010 | en_HK |
dc.identifier.citation | Canadian Journal Of Statistics, 2010, v. 38 n. 4, p. 665-679 | en_HK |
dc.identifier.issn | 0319-5724 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/129371 | - |
dc.description.abstract | For 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.language | eng | en_US |
dc.publisher | Statistical Society of Canada. The Journal's web site is located at http://www.mat.ulaval.ca/cjs | en_HK |
dc.relation.ispartof | Canadian Journal of Statistics | en_HK |
dc.subject | Identifiability | en_HK |
dc.subject | Median regression | en_HK |
dc.subject | Residual lifetime | en_HK |
dc.subject | Semiparametric model | en_HK |
dc.subject | Survival function | en_HK |
dc.title | Semiparametric median residual life model and inference | en_HK |
dc.type | Article | en_HK |
dc.identifier.openurl | http://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.email | Yin, G: gyin@hku.hk | en_HK |
dc.identifier.authority | Yin, G=rp00831 | en_HK |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1002/cjs.10076 | en_HK |
dc.identifier.scopus | eid_2-s2.0-78149364862 | en_HK |
dc.identifier.hkuros | 177204 | en_US |
dc.identifier.hkuros | 195656 | - |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-78149364862&selection=ref&src=s&origin=recordpage | en_HK |
dc.identifier.volume | 38 | en_HK |
dc.identifier.issue | 4 | en_HK |
dc.identifier.spage | 665 | en_HK |
dc.identifier.epage | 679 | en_HK |
dc.identifier.isi | WOS:000284674900009 | - |
dc.publisher.place | Canada | en_HK |
dc.identifier.scopusauthorid | Ma, Y=8908626500 | en_HK |
dc.identifier.scopusauthorid | Yin, G=8725807500 | en_HK |
dc.identifier.issnl | 0319-5724 | - |