部分线性测量误差模型中的估计问题

详细信息

Estimation for Partially Linear Errors-in-Variable Models

College of Mathematics and Statistics,Shenzhen University, Shenzhen, 518060, China
Shen Zhen-Hong Kong Joint Research Center for Applied Statistical Sciences Shenzhen University, Shenzhen, 518060, China
Institute of Statistical Sciences, Shenzhen University, Shenzhen, 518060, China

Funds: Jun Zhang's research was supported by the National Natural Science Foundation of China (Grant No. 11401391).

摘要: 本文考虑了部分线性模型中非参数部分带有可加测量误差的估计问题. 本文提出了两种估计方法, 第一种是基于逆卷积的积分矩估计方法, 给出该估计的强相合收敛性. 第二种是基于模拟的估计方法, 该方法避免了积分矩估计方法中的积分问题. 最后本文用一些数值结果来说明估计方法的估计效果.
- 逆卷积 /
- 测量误差模型 /
- 部分线性模型 /
- 重复测量误差数据
Abstract: In this paper, we consider the estimation problem for partially linear models with additive measurement errors in the nonparametric part. Two kinds of estimators are proposed. The first one is an integral moment-based estimator with deconvolution kernel techniques, associated with the strong consistency for the estimator. Another one is a simulation-based estimator to avoid the integrals involved in the integral moment-based estimator. Simulation studies are conducted to examine the performance of the proposed estimators.
- deconvolution /
- errors-in-variables /
- partial linear models /
- replicated measurement error data