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Smothing Spline Estimation for Nonparametric Model of Longitudinal Data

??In the last few decades, longitudinal data was deeply researchin statistics science and widely used in many field, such as finance, medical science,agriculture and so on. The characteristic of longitudinal data is that the values areindependent from different samples but they are correlate from one sample. Manynonparametric estimation methods were applied into longitudinal data models with developmentof computer technology. Using Cholesky decomposition and Profile least squares estimation,we will propose a effective spline estimation method pointing at nonparametric model oflongitudinal data with covariance matrix unknown in this paper. Finally, we point thatthe new proposed method is more superior than Naive spline estimation in the covariancematrix is unknown case by comparing the simulated results of one example.