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For: Li J, Xia Y, Palta M, Shankar A. Impact of unknown covariance structures in semiparametric models for longitudinal data: An application to Wisconsin diabetes data. Comput Stat Data Anal 2009. [DOI: 10.1016/j.csda.2009.05.008] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Number Cited by Other Article(s)
1
Huang T, Li J. Semiparametric model average prediction in panel data analysis. J Nonparametr Stat 2017. [DOI: 10.1080/10485252.2017.1404061] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
2
Huang Z, Li J, Nott D, Feng L, Ng TP, Wong TY. Bayesian estimation of varying-coefficient models with missing data, with application to the Singapore Longitudinal Aging Study. J STAT COMPUT SIM 2014. [DOI: 10.1080/00949655.2014.928821] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
3
Park JH. Analysing nonlinear time series with central subspace. J STAT COMPUT SIM 2012. [DOI: 10.1080/00949655.2011.571688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
4
Chen Z, Shi NZ, Gao W, Tang ML. Efficient semiparametric estimation via Cholesky decomposition for longitudinal data. Comput Stat Data Anal 2011. [DOI: 10.1016/j.csda.2011.06.025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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