Non parametric regression analysis for longitudinal data with time-depending autoregressive error process

References

• Bai, Y., J. Huang, R. Li, and J. You. 2015. Semiparametric longitudinal model with irregular time autoregressive error process. Statistica Sinica 25:507–27.
   Web of Science ®Google Scholar
• Cardot, H. 2007. Conditional functional principal components analysis. Scandinavian Journal of Statistics 40(2):317–35.
   Google Scholar
• Diggle, P. J., and A. P. Verbyla. 1998. Nonparametric estimation of covariance structure in longitudinal data. Biometrics 54 (2):401–15.
   PubMed Web of Science ®Google Scholar
• Fan, J., and I. Gijbels. 1998. Local polynomial modelling and its applications. London: Chapman and Hall.
   Google Scholar
• Fan, J., T. Huang, and R. Li. 2007. Analysis of longitudinal data with semiparametric estimation of covariance function. Journal of the American Statistical Association 34 (2):632–41.
   Web of Science ®Google Scholar
• Fan, J., and Y. Wu. 2008. Semiparametric estimation of covariance matrices for longitudinal data. Journal of the American Statistical Association 103 (484):1520–33.
   PubMed Web of Science ®Google Scholar
• Gu, J., Q. Li, and J.-C Yang. 2015. Multivariate local polynomial kernel estimators: Leading bias and asymptotic distribution. Econometric Reviews 34 (6–10): 979–1010.
   Web of Science ®Google Scholar
• Hansen, L. P.. 1982. Large sample properties of generalized method of moments estimators. Econometrica 50 (4):1029–54.
   Web of Science ®Google Scholar
• Huang, J. Z., L. Liu, and N., Liu. 2007. Estimation of large covariance matrices of longitudinal data with basis function approximations. Journal of Computational and Graphical Statistics 16 (1):189–209.
   Web of Science ®Google Scholar
• Jiang, C.-R., and J.-L. Wang. 2010. Covariate adjusted functional principal components analysis for longitudinal data. The Annals of Statistics. 38 (2):1194–226.
   Web of Science ®Google Scholar
• Leng, C., W. Zhang, and P., Jianxin. 2010. Semiparametric meancovariance regression analysis for longitudinal data. Journal of the American Statistical Association 105 (489):181–93.
   Web of Science ®Google Scholar
• Li, Y.. 2011. Efficient semiparametric regression for longitudinal data with nonparametric covariance estimation. Biometrika 98 (2):355–70.
   Web of Science ®Google Scholar
• Liang, H., W. Hardle, and R. J. Carroll. 1999. Estimation in a semiparametric partially linear errors-in-variables model. The Annals of Statistics 27 (5):1519–35.
   Web of Science ®Google Scholar
• Liang, H., and H. Wu. 2003. The relationship between virologic and immunologic responses in aids clinical research using mixed-effects varying-coefficient models with measurement error. Biostatistics 4 (2):297–312.
   PubMed 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.
   Web of Science ®Google Scholar
• Lin, X., and R. J. Carroll. 2000. Nonparametric function estimation for clustered data when the predictor is measured without/with error. Journal of the American Statistical Association 95 (450):520–34.
   Web of Science ®Google Scholar
• Linton, O. B., E. Mammen, X. Lin, and R. J. Carroll. 2003. Accounting for correlation in marginal longitudinal nonparametric regression. In: Lin, D. Y., P. J. Heagerty. (Eds.), Proceedings of the Second Seattle Symposium in Biostatistics: Analysis of Correlated Data. New York: Springer, pp. 23–33.
   Google Scholar
• Masry, E.. 1996. Multivariate local polynomial regression for time series: Uniform strong consistency and rates. Journal of Time Series Analysis 17 (6):571–99.
   Google Scholar
• Qu, A., B. G. Lindsay, and B. Li, 2000. Improving generalised estimating equations using quadratic inference functions. Biometrika 87 (4):823–36.
   Web of Science ®Google Scholar
• Rice, J. A., and C. O. Wu. 2002. Nonparametric mixed effects models for unequally sampled noisy curves. Biometrics 97 (458):482–93.
   Google Scholar
• Welch, A. H., X. Lin, and R. J. Carroll. 2002. Marginal longitudinal nonparametric regression: Locality and efficiency of spline and kernel methods. Journal of the American Statistical Association 97 (458): 482–93.
   Web of Science ®Google Scholar
• Wu, H., and H. Liang. 2004. Backfitting random varying-coefficient models with time-dependent smoothingcovariates. Scandinavian Journal of Statistics 31 (1):3–19.
   Web of Science ®Google Scholar