Kong D.*, Xue, K.*, Yao, F., and Zhang, H. H. (2016). Partially functional linear regression in high dimensions (supplemental material). Biometrika, onlie doi: 10.1093/biomet/asv062.

Yao, F., Lei, E.*, and Wu, Y. (2015). Effective dimension reduction for sparse functional data. Biometrika, online doi: 10.1093/biomet/asv006.

Lei, E.*, Yao, F., Heckman, N, and Meyer, K. (2015). Functional data model for genetically related individuals with application to cow growth. Journal of Computational and Graphical Statistics, online doi:10.1080/10618600.2014.948180.

Zhu, H.*, Yao, F., and Zhang, H. H. (2014). Structured functional additive regression in reproducing kernel Hilbert spaces. Journal of the Royal Statistical Society, Series B, 76, 581-603.

Li, L*, Yao, F., Craiu, R. V., and Zou, J* (2014). Minimum description length principle for linear mixed effects models. Statistica Sinica, 24, 1161-1178.

Wong, R. K. W.*, Yao, F., and Lee, T. C. M. (2014). Robust estimation for generalized additive models. Journal of Computational and Graphical Statistics, 23, 270-289.

Acar, E.*, Craiu, R. V., and Yao, F. (2013). Statistical tesing of covariate effects in conditional copula models. Electronic Journal of Statistics, 7, 2822-2850.

Müller, H. G., Wu, Y., and Yao, F. (2013). Continuously additive models for nonlinear functional regression. Biometrika, 100, 607-622.

Acar, E.*, Craiu, R. V., and Yao, F. (2011). Dependence calibration in conditional copulas: a nonparametric approach (web appendix). Biometrics, 67, 445-453.

Yao, F., Fu, Y., and Lee, T. C. M. (2011). Functional mixture regression (web appendix). Biostatistics, 12, 341-353.

Müller, H. G., and Yao, F. (2010). Additive modeling of functional gradients. Biometrika, 97, 791-805.

Müller, H. G., and Yao, F. (2010). Empirical dynamics for longitudinal data. The Annals of Statistics, 38, 3458-3486.

Lai, R. C. S.*, Lee, T. C. M., Wong, R.  K. W.*, and Yao, F. (2010). Nonparametric cepstrum estimation via optimal risk smoothing, IEEE Transactions on Signal Processing, 58, 1507-1514.

Yao, F., and Müller, H. G. (2010). Functional quadratic regression. Biometrika, 97, 49-64.

Yao, F., Craiu, R. V., and Reiser, B. (2010). Nonparametric covariate adjustment for receiver operating characteristic curves. Canadian Journal of Statistics, 38, 27-46.

Yao, F., and Lee, T. C. M. (2009). Automatic and asymptotically optimal data sharpening for nonparametric regression. Journal of Statistical Planning and Inference, 139, 4017-4030.

Hall, P., Müller, H. G., and Yao, F. (2009). Estimation of functional derivatives. The Annals of Statistics, 37, 3307-3329.

Zou, S., Carey, J. R., Liedo, P., Ingram, D. K., Müller, H. G., Wang, J. L., Yao, F., Yu, B., and Zhou, A. (2009). The prolongevity effect of resveratrol depends on dietary composition and calorie intake in a tephritid fruit fly. Experimental Gerontology, 44, 472-476.

Müller, H. G., and Yao, F. (2008). Functional additive models. Journal of American Statistical Association, 103, 1534-1544.

Hall, P., Müller, H. G., and Yao, F. (2008). Modeling sparse generalized longitudinal observations with latent Gaussian processes. Journal of the Royal Statistical Society, Series B, 70, 703-723.

Yao, F, and Lee, T. C. M. (2008). On knot placement for penalized spline regression. Journal of the Korean Statistical Society, 37, 259-267.

Yao, F. (2008). Functional approach of flexibly modelling generalized longitudinal data and survival time. Journal of Statistical Planning and Inference, 138, 995-1009.

Yao, F. (2007). Functional principal component analysis for longitudinal and survival data. Statistica Sinica, 17, 965-983.

Yao, F, and Lee, T. C. M. (2007). Spectral density estimation using sharpened periodograms. IEEE Transactions on Signal Processing, 55, 4711-4716.

Yao. F. (2007). Asymptotic distributions of nonparametric regression estimators for longitudinal or functional data. Journal of Multivariate Analysis, 98, 40-56.

Müller, H. G., Stadtmüller, U., and Yao, F. (2006). Functional variance processes. Journal of American Statistical Association, 101, 1007-1018.

Yao, F., and Lee, T. C. M. (2006). Penalized spline models for functional principal component analysis. Journal of the Royal Statistical Society, Series B, 68, 3-25.

Müller, H. G., and Yao, F. (2006). Regressing longitudinal response trajectories on a covariate. In Frontiers of Statistics: Festschrift for Peter Bickel (Eds.  J. Fan and H. Koul). London: Imperial College Press.

Yao, F., Müller, H. G., and Wang, J. L. (2005). Functional linear regression analysis for longitudinal data. The Annals of Statistics, 33, 2873-2903.

Yao, F., Müller, H. G. and Wang, J. L. (2005). Functional data analysis for sparse longitudinal data. Journal of the American Statistical Association, 100, 577-590.

Müller, H. G., Wang, J. L., Carey, J. R., Caswell-Chen, E. P., Chen, C., Papadopoulos, N., and Yao, F. (2004). Demographic window to aging in the wild: Constructing life tables and  estimating survival functions from marked individuals of unknown age. Aging Cell, 3, 125-131.

Yao, F., Müller, H. G., Clifford, A. J., Dueker, S. R., Follett, J., Lin, Y., Buchholz, B. A., and Vogel, J. S. (2003). Shrinkage estimation for functional principal component scores with application to the population kinetics of plasma folate. Biometrics, 59, 676-685.