基于sieve方法的响应变量为当前状态数据的部分函数型线性模型的估计

Estimator for partial functional linear model with current status data based on sieve method

利用sieve方法研究响应变量为当前状态数据的部分函数型线性模型的估计.在一定的条件下,证明了该估计的强相合性和渐近正态性,得到了该估计的收敛速度,并且非参数部分达到最优收敛速度.最后通过一个数值模拟来研究该估计的有限样本性质.

In this paper, sieve method is used to obtain the estimators for partial functional linear model with current status data. Under some mild conditions, the estimators are proved to be strong consistent and asymptotically normally distributed, and the convergence rate of the estimators is obtained and the nonparametric part of the estimators has an optimal convergence rate. Finally, a simulation study is carried out to illustrate the ˉnite sample properties of our proposed estimators.