Baìllo, A., and A. Grané. 2009. Local linear regression for functional predictor and scalar response. Journal of Multivariate Analysis 100:102–11.
Barrientos-Marin, J., F. Ferraty, and P. Vieu. 2010. Locally modelled regression and functional data. Journal of Nonparametric Statistics 22:617–32.
Berlinet, A., A. Elamine, and A. Mas. 2011. Local linear regression for functional data. Annals of the Institute of Statistical Mathematics 63:104–75.
Bosq, D. 2000. Linear processes in function spaces. Theory and applications. Lecture Notes in Statistics, 149. New York: Springer-Verlag.
Burba F., F. Ferraty, and P. Vieu. 2009. k-nearest neighbor method in functional nonparametric regression. Journal of Nonparametric Statistics 21:453–69.
Chen, J., and L. Zhang. 2009. Asymptotic properties of nonparametric M-estimation for mixing functional data. Journal of Statistical Planning and Inference 139:533–46.
Cuevas, A. 2014. A partial overview of the theory of statistics with functional data. Journal of Statistical Planning and Inference 147:1–23.
Demongeot, J., A. Hamie, A. Laksaci, and M. Rachdi. 2016. Relative-error prediction in nonparametric functional statistics: Theory and practice. Journal of Multivariate Analysis 146:261–68
Fan, J., Q. Yao, and H. Tong. 1996. Estimation of conditional densities and senscitivity measures in nonlinear dynamical systems. Biometrika 83:189–206.
Ferraty, F., A. Laksaci, A. Tadj, and P. Vieu. 2010. Rate of uniform consistency for nonparametric estimates with functional variables. Journal of Statistical Planning and Inference 140:335–52.
Ferraty, F., and P. Vieu. 2006. Nonparametric functional data analysis. Theory and practice. Springer Series in Statistics. New York, NY: Springer.
Goia, A., and P. Vieu. 2016. An introduction to recent advances in high/infinite dimensional statistics. Journal of Multivariate Analysis 146:1–6.
Hallin, M., Z. Lu, and K. Yu. 2009. Local linear spatial quantile regression. Bernoulli 15:659–86.
Hsing, T., and R. Eubank, 2015. Theoretical foundations of functional data analysis, with an introduction to linear operators. Wiley Series in Probability and Statistics. Chichester, UK: John Wiley & Sons.
Jones, M. C., H. Park, K. L. Shin, S. K. Vines, and S. O. Jeong. 2008. Relative error prediction via kernel regression smoothers. Journal of Statistical Planning and Inference 138:2887–98.
Masry, E. 1996. Multivariate local polynomial regression for time series: Uniform strong consistency and rates. Journal of Time Series Analysis 17:571–99.
Narula, S. C., and J. F. Wellington. 1977. Prediction, linear regression and the minimum sum of relative errors. Technometrics 19:185–90.
Ramsay, J. O., and B. W. Silverman. 2002. Applied functional data analysis. Methods and case studies. Springer Series in Statistics. New York, NY: Springer.
Sarda, P., and P. Vieu. 2000. Kernel regression. In Smoothing and regression. Approaches, computation and application, ed. M. G. Schimek, 43–70. Wiley Series in Probability and Statistics, New York. Chichester: Wiley.
Stone, C. J. 1977. Consistent nonparametric regression. Discussion. Annals of Statistics 5:595–645.
Yang, Y., and F. Ye. 2013. General relative error criterion and M-estimation. Frontriers of Mathematics in China 8:695–715.
Zhang, J. 2013. Analysis of variance for functional data. Boca Raton, FL: Chapman & Hall/CRC, Monographs on Statistics & Applied Probability.
Zhou, Z., and Z. Lin. 2016. Asymptotic normality of locally modelled regression estimator for functional data. Journal of Nonparametric Statistics 28:116–131.