Please use this identifier to cite or link to this item: https://doi.org/10.1093/biomet/asr068
DC FieldValue
dc.titleA moving average Cholesky factor model in covariance modelling for longitudinal data
dc.contributor.authorZhang, W.
dc.contributor.authorLeng, C.
dc.date.accessioned2014-10-28T05:09:16Z
dc.date.available2014-10-28T05:09:16Z
dc.date.issued2012-03
dc.identifier.citationZhang, W., Leng, C. (2012-03). A moving average Cholesky factor model in covariance modelling for longitudinal data. Biometrika 99 (1) : 141-150. ScholarBank@NUS Repository. https://doi.org/10.1093/biomet/asr068
dc.identifier.issn00063444
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/104942
dc.description.abstractWe propose new regression models for parameterizing covariance structures in longitudinal data analysis. Using a novel Cholesky factor, the entries in this decomposition have a moving average and log-innovation interpretation and are modelled as linear functions of covariates. We propose efficient maximum likelihood estimates for joint mean-covariance analysis based on this decomposition and derive the asymptotic distributions of the coefficient estimates. Furthermore, we study a local search algorithm, computationally more efficient than traditional all subset selection, based on bic for model selection, and show its model selection consistency. Thus, a conjecture of Pan & MacKenzie (2003) is verified. We demonstrate the finite-sample performance of the method via analysis of data on CD4 trajectories and through simulations. © 2011 Biometrika Trust.
dc.sourceScopus
dc.subjectbic
dc.subjectLongitudinal data analysis
dc.subjectMaximum likelihood estimation
dc.subjectModel selection
dc.subjectModified Cholesky decomposition
dc.subjectMoving average
dc.typeArticle
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1093/biomet/asr068
dc.description.sourcetitleBiometrika
dc.description.volume99
dc.description.issue1
dc.description.page141-150
dc.description.codenBIOKA
dc.identifier.isiut000300734400011
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

58
checked on Nov 29, 2022

WEB OF SCIENCETM
Citations

56
checked on Nov 29, 2022

Page view(s)

185
checked on Nov 24, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.