Estimation in partially linear models with missing responses at random
Estimation in partially linear models with missing responses at random
复制标题
随机缺失响应的部分线性模型中的估计
DOI：
10.1016/j.jmva.2006.10.003
复制
发表时间：
2007-08-01
影响因子：
1.6
通讯作者：
Sun, Zhihua
中科院分区：
文献类型：
--
作者：
Wang, Qihua;Sun, Zhihua
当响应随机缺失时，考虑部分线性模型。分别用插补法、半参数回归替代法和逆边际概率加权法估计回归系数和非参数函数。证明了回归系数的估计是渐近正态的，非参数函数的估计是以最优速度收敛的。进行了模拟研究，以比较所提出的估计的有限样本行为。(c)2006年爱思唯尔公司All rights reserved.
A partially linear model is considered when the responses are missing at random. Imputation, semiparametric regression surrogate and inverse marginal probability weighted approaches are developed to estimate the regression coefficients and the nonparametric function, respectively. All the proposed estimators for the regression coefficients are shown to be asymptotically normal, and the estimators for the nonparametric function are proved to converge at an optimal rate. A simulation study is conducted to compare the finite sample behavior of the proposed estimators. (c) 2006 Elsevier Inc. All rights reserved.