数学
经验似然
估计员
正交性
应用数学
非参数统计
协变量
收敛速度
推论
统计推断
参数统计
统计
计算机科学
计算机网络
频道(广播)
几何学
人工智能
作者
Yan Zhou,R.D. van der Mei,Yichuan Zhao,Zongliang Hu,Mingtao Zhao
标识
DOI:10.1016/j.cam.2023.115751
摘要
In this paper, we study the model estimation for the partial linear varying coefficient errors-in-variables (EV) models with longitudinal data. Based on the empirical likelihood and quadratic inference functions (QIF), we propose an orthogonality-based bias-corrected empirical likelihood estimation method using the orthogonal decomposition (QR) method of matrix. The proposed method can handle the measurement errors of covariates and unknown within-subject correlation simultaneously, estimate the parametric and nonparametric components separately. Under some regularity conditions, the resulting estimator of the parametric component is asymptotic normal and the estimators of the nonparametric varying coefficients achieve the optimal convergence rate. Furthermore, we conduct simulation studies and a real data analysis to compare the performance of the proposed method and existing methods in finite samples. The results show that the feasibility of the proposed method is obvious.
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