Acta mathematica scientia,Series A ›› 2020, Vol. 40 ›› Issue (2): 460-474.

Previous Articles     Next Articles

Statistical Inference in Partially Nonlinear Varying-Coefficient Errors-in-Variables Models with Missing Responses

Yijia Ma*(),Liugen Xue,Fei Lu   

  1. College of Applied Sciences, Beijing University of Technology, Beijing 100124
  • Received:2018-05-18 Online:2020-04-26 Published:2020-05-21
  • Contact: Yijia Ma E-mail:redbamboo12138@126.com
  • Supported by:
    the NSFC(11971001);the Beijing Natural Science Foundation(1182002)

Abstract:

This paper considers about the estimation of varying-coefficient partial nonlinear errors-in-variables models with missing responses. Firstly, we develop inverse probability weighted approaches and local bias-corrected restricted profile least squares estimators. Asymptotic normality of estimators is established. Moreover, both simulation results and a real data show that local bias-corrected restricted profile least squares estimated approach are better than the performance ignoring the measurement error.

Key words: Varying-coefficient partial nonlinear model, Missing data, Local bias-corrected restricted profile least-squares approach, Measurement error, Asymptotic normality

CLC Number: 

  • O212.7
Trendmd