部分线性模型的统一估计的强相合性

Strong consistent of unified estimation for semiparametric partially linear regression models

在纵向数据研究中,要求对个体的观测为稀疏的,在函数型数据研究中,要求对个体的观测为稠密的,为了抛弃这些限制性的条件,考虑部分线性模型,对函数型数据和纵向数据的半参数部分线性模型提出了一种统一的估计方法,并证明了估计的强相合性,在提出的估计中,个体的观测数目是完全灵活的,克服了以前方法的缺点.

In the context of longitudinal data analysis, a random function typically represents a subject that is often observed at sparse time point. In the context of functional data analysis, a random function typically represents a subject that is often observed at dense time point. In dealing with real data, it may even be difficult to classify which scenario we are faced with and hence to decide which methodology to use. In this paper, we proposed a unified estimation for the semiparametric partially linear regression model, and studied the strong consistent of the proposed estimators.