Penalized Likelihood Estimation of a Class of Zero-Inflated Semiparametric Mixed-Effect Model

In this paper, we consider an extension of semiparametric linear mixed-effect model to a class of longitudinal data or clustered data with zero-inflation and propose a novel semiparametric mixed model. Based on the maximum penalized likelihood estimation and EM algorithm, we give a method for our proposed model which may estimate both of the parameters and nonparameters simultaneously. In the method, we use GCV to choose the smoothing parameter.Finally, we study a simulation analysis and one real data set to illustrate the proposed method.