Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/30559
DC FieldValueLanguage
dc.contributorDepartment of Applied Mathematics-
dc.creatorSun, L-
dc.creatorZhou, X-
dc.date.accessioned2015-06-23T09:12:38Z-
dc.date.available2015-06-23T09:12:38Z-
dc.identifier.issn0167-7152-
dc.identifier.urihttp://hdl.handle.net/10397/30559-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectCounting processen_US
dc.subjectPanel studiesen_US
dc.subjectRepeated measurementsen_US
dc.subjectSemiparametric modellingen_US
dc.subjectTime-dependent covariateen_US
dc.titleRegression analysis for a semiparametric model with panel dataen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage309-
dc.identifier.epage317-
dc.identifier.volume58-
dc.identifier.issue3-
dc.identifier.doi10.1016/S0167-7152(02)00147-5-
dcterms.abstractIn a longitudinal study, suppose that for each subject, repeated measurements of the response variable and covariates are collected at a set of distinct, irregularly spaced time points. In this paper, we consider a semiparametric model to analyse such panel data. The model specifies that the mean of the response variable at each time point is the sum of the baseline mean function and the regression function of time-dependent covariates. Simple procedures for regression parameters are proposed without involving any nonparametric function estimation for the nuisance mean function. Extensive simulation studies are used to show that our estimators perform well in finite samples.-
dcterms.bibliographicCitationStatistics and probability letters, 2002, v. 58, no. 3, p. 309-317-
dcterms.isPartOfStatistics and Probability Letters-
dcterms.issued2002-
dc.identifier.isiWOS:000177319000009-
dc.identifier.scopus2-s2.0-0036639862-
dc.identifier.rosgroupidr09712-
dc.description.ros2001-2002 > Academic research: refereed > Publication in refereed journal-
Appears in Collections:Journal/Magazine Article
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