Focused information criterion and model averaging for varying-coefficient partially linear models with longitudinal data

References

• Ahmad, I., S. Leelahanon, and Q. Li. 2005. Efficient estimation of a semiparametric partially linear varying coefficient model. The Annals of Statistics 33 (1):258–83. doi:10.1214/009053604000000931.
   Web of Science ®Google Scholar
• Akaike, H. 1973. Maximum likelihood identification of Gaussian autoregressive moving average models. Biometrika 60 (2):255–65. doi:10.2307/2334537.
   Web of Science ®Google Scholar
• Behl, P., G. Claeskens, and H. Dette. 2014. Focussed model selection in quantile regression. Statistica Sinica 24:601–24.
   Web of Science ®Google Scholar
• Buckland, S. T., K. P. Burnham, and N. H. Augustin. 1997. Model selection: an integral part of inference. Biometrics 53 (2):603–18. doi:10.2307/2533961.
   Web of Science ®Google Scholar
• Cantoni, E., J. M. Flemming, and E. Ronchetti. 2005. Variable selection for marginal longitudinal generalized linear models. Biometrics 61 (2):507–14. doi:10.1111/j.1541-0420.2005.00331.x.
   PubMed Web of Science ®Google Scholar
• Chang, M., and F. J. DiTraglia. 2018. A generalized focused information criterion for GMM. Journal of Applied Econometrics 33 (3):378–97. doi:10.1002/jae.2614.
   Web of Science ®Google Scholar
• Cheng, G., L. Zhou, and J. Z. Huang. 2014. Efficient semiparametric estimation in generalized partially linear additive models for longitudinal/clustered data. Bernoulli 20 (1):141–63. doi:10.3150/12-BEJ479.
   Web of Science ®Google Scholar
• Cheng, M., T. Honda, and J. Li. 2016. Efficient estimation in semivarying coefficient models for longitudinal/clustered data. The Annals of Statistics 44 (5):1988–2017. doi:10.1214/15-AOS1385.
   Web of Science ®Google Scholar
• Claeskens, G., C. Croux, and J. Van Kerckhoven. 2006. Variable selection for logistic regression using a prediction-focused information criterion. Biometrics 62 (4):972–9. doi:10.1111/j.1541-0420.2006.00567.x.
   PubMed Web of Science ®Google Scholar
• Claeskens, G., and N. L. Hjort. 2003. The focused information criterion (with discussion). Journal of the American Statistical Association 98 (464):900–16. doi:10.1198/016214503000000819.
   Web of Science ®Google Scholar
• Claeskens, G., and N. L. Hjort. 2008. Model selection and model averaging. New York: Cambridge University Press.
   Google Scholar
• Fan, J., and J. Zhang. 2000. Two-step estimation of functional linear models with applications to longitudinal data. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 62 (2):303–22. doi:10.1111/1467-9868.00233.
   Web of Science ®Google Scholar
• Fan, J., and R. Li. 2004. New estimation and model selection procedures for semiparametric modeling in longitudinal data analysis. Journal of the American Statistical Association 99 (467):710–23. doi:10.1198/016214504000001060.
   Web of Science ®Google Scholar
• Fan, J., and T. Huang. 2005. Profile likelihood inferences on semiparametric varying-coefficient partially linear models. Bernoulli 11 (6):1031–57. doi:10.3150/bj/1137421639.
   Web of Science ®Google Scholar
• Fan, J., Y. Ma, and W. Dai. 2014. Nonparametric independence screening in sparse ultra-high-dimensional varying coefficient models. Journal of the American Statistical Association 109 (507):1270–84. doi:10.1080/01621459.2013.879828.
   PubMed Web of Science ®Google Scholar
• Gao, Y., X. Zhang, S. Wang, and G. Zou. 2016. Model averaging based on leave-subject-out cross-validation. Journal of Econometrics 192 (1):139–51. doi:10.1016/j.jeconom.2015.07.006.
   Web of Science ®Google Scholar
• Gueuning, T., and G. Claeskens. 2018. A high-dimensional focused information criterion. Scandinavian Journal of Statistics 45 (1):34–61. doi:10.1111/sjos.12285.
   Web of Science ®Google Scholar
• Hjort, N. L., and G. Claeskens. 2003. Frequentist model average estimators. Journal of the American Statistical Association 98 (464):879–99. doi:10.1198/016214503000000828.
   Web of Science ®Google Scholar
• Hjort, N. L., and G. Claeskens. 2006. Focussed information criteria and model averaging for Cox’s hazard regression model. Journal of the American Statistical Association 101 (476):1449–64. doi:10.1198/016214506000000069.
   Web of Science ®Google Scholar
• Huang, J. Z., C. O. Wu, and L. Zhou. 2002. Varying coefficient models and basis function approximation for the analysis of repeated measurements. Biometrika 89 (1):111–28. doi:10.1093/biomet/89.1.111.
   Web of Science ®Google Scholar
• Huang, J. Z., C. O. Wu, and L. Zhou. 2004. Polynomial spline estimation and inference for varying coefficient models with longitudinal data. Statistica Sinica 14:763–88.
   Web of Science ®Google Scholar
• Huang, J. Z., L. Zhang, and L. Zhou. 2007. Efficient estimation in marginal partially linear models for longitudinal/clustered data using splines. Scandinavian Journal of Statistics 34 (3):451–77. doi:10.1111/j.1467-9469.2006.00550.x.
   Web of Science ®Google Scholar
• Liang, K. Y., and S. L. Zeger. 1986. Longitudinal data analysis using generalized linear models. Biometrika 73 (1):13–22. doi:10.2307/2336267.
   Web of Science ®Google Scholar
• Lin, D. Y., and Z. Ying. 2001. Semiparametric and nonparametric regression analysis of longitudinal data. Journal of the American Statistical Association 96 (453):103–12. doi:10.1198/016214501750333018.
   Web of Science ®Google Scholar
• Pan, W. 2001. Akaike’s information criterion in generalized estimating equations. Biometrics 57 (1):120–5. doi:10.1111/j.0006-341X.2001.00120.x.
   PubMed Web of Science ®Google Scholar
• Qu, A., B. G. Lindsay, and B. Li. 2000. Improving generalized estimating equations and quadratic inference functions. Biometrika 87 (4):823–36. doi:10.1093/biomet/87.4.823.
   Web of Science ®Google Scholar
• Qu, A., and P. X. K. Song. 2004. Assessing robustness of generalised estimating equations and quadratic inference functions. Biometrika 91 (2):447–59. doi:10.1093/biomet/91.2.447.
   Web of Science ®Google Scholar
• Schwarz, G. 1978. Estimating the dimension of a model. The Annals of Statistics 6 (2):461–4. doi:10.1214/aos/1176344136.
   Web of Science ®Google Scholar
• Stone, C. J. 1982. Optimal global rates of convergence for nonparametric regression. The Annals of Statistics 10:1348–60.
   Web of Science ®Google Scholar
• Wang, H., Y. Li, and J. Sun. 2015. Focused and model average estimation for regression analysis of panel count data. Scandinavian Journal of Statistics 42 (3):732–45. doi:10.1111/sjos.12133.
   Web of Science ®Google Scholar
• Wang, N., R. J. Carroll, and X. Lin. 2005. Efficient semiparametric marginal estimation for longitudinal/clustered data. Journal of the American Statistical Association 100 (469):147–57. doi:10.1198/016214504000000629.
   Web of Science ®Google Scholar
• Yang, H., P. Lin, G. Zou, and H. Liang. 2017. Variable selection and model averaging for longitudinal data incorporating GEE approach. Statistica Sinica 27:389–413.
   Web of Science ®Google Scholar
• Zhang, Q., X. Duan, and S. Ma. 2017. Focused information criterion and model averaging with generalized rank regression. Statistics & Probability Letters 122:11–9. doi:10.1016/j.spl.2016.10.020.
   PubMed Web of Science ®Google Scholar
• Zhang, W., S. Y. Lee, and X. Song. 2002. Local polynomial fitting in semiparametric coefficient model. Journal of Multivariate Analysis 82 (1):166–88. doi:10.1006/jmva.2001.2012.
   Web of Science ®Google Scholar
• Zhang, X., A. T. K. Wan, and S. Zhou. 2012. Focused information criteria, model selection, and model averaging in a Tobit Model with a nonzero threshold. Journal of Business & Economic Statistics 30:132–42. doi:10.1198/jbes.2011.10075.
   Web of Science ®Google Scholar
• Zhang, X., G. Zou, and H. Liang. 2014. Model averaging and weight choice in linear mixed-effects models. Biometrika 101 (1):205–18. doi:10.1093/biomet/ast052.
   Web of Science ®Google Scholar
• Zhang, X., and H. Liang. 2011. Focused information criterion and model averaging for generalized additive partial linear models. The Annals of Statistics 39 (1):174–200. doi:10.1214/10-AOS832.
   Web of Science ®Google Scholar