QR decomposition based orthogonality estimation for partially linear models with longitudinal data

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摘要

This paper studies the estimation for a class of partially linear models with longitudinal data. By combining quadratic inference functions with QR decomposition technology, we propose a new estimation method for the parametric and nonparametric components. The resulting estimators for parametric and nonparametric components do not affect each other, and then it is easy for application in practice. Under some mild conditions, we establish some asymptotic properties of the resulting estimators. Some simulation studies are undertaken to assess the finite sample performance of the proposed estimation procedure.

论文关键词:62G05,62G20,62G30,Partially linear model,Longitudinal data,Orthogonality estimation,QR decomposition

论文评审过程:Received 21 December 2016, Available online 9 March 2017, Version of Record 25 March 2017.

论文官网地址:https://doi.org/10.1016/j.cam.2017.02.024