Efficient Estimation of the Nonparametric Mean and Covariance Functions for Longitudinal and Sparse Functional Data
提出一种改进的局部核平滑方法，结合准似然估计纵向和稀疏函数数据的均值与协方差函数，证明估计量具有相合性、渐近正态性和半参数有效性，并通过模拟和实际数据分析（艾滋病研究、大气研究）验证其优越性。
We consider the estimation of mean and covariance functions for longitudinal and sparse functional data by using the full quasi-likelihood coupling a modification of the local kernel smoothing method. The proposed estimators are shown to be consistent, asymptotically normal, and semiparametrically efficient in terms of their linear functionals. Their superiority to the competitors is further illustrated numerically through simulation studies. The method is applied to analyze AIDS study and atmospheric study. Supplementary materials for this article are available online.