Partial Linear Models for Longitudinal Data Based on Penalized General Method of Moments

For the analysis of partial linear model with longitudinal data, the general procedure is to fit the nonparametric part with kernel or spline estimation, followed by generalized linear model estimating frame. In this paper, we fit the nonparametric part with P-spline, and estimate the parametrical and nonparametric part with different Generalized method of moments estimation for different moment conditions, implemented by the proof of the asymptotical properties for the estimator, which is also been proved by simulation and illustrative example, from which we can also find out that different penalized general method of moments estimations for different moment conditions perform more efficiently.