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An improved and efficient estimation method for varying-coefficient model with missing covariates

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  • Sun, Jing
  • Sun, Qihang

Abstract

For the coefficient functions of varying-coefficient models with missing covariates, we develop weighted quantile average estimation and obtain the optimal weights whose corresponding estimate approaches the Cramér–Rao lower bound under appropriate regularity conditions. Theoretical and simulation results show the good performance of our method.

Suggested Citation

  • Sun, Jing & Sun, Qihang, 2015. "An improved and efficient estimation method for varying-coefficient model with missing covariates," Statistics & Probability Letters, Elsevier, vol. 107(C), pages 296-303.
    • Handle: RePEc:eee:stapro:v:107:y:2015:i:c:p:296-303
    DOI: 10.1016/j.spl.2015.09.009
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    References listed on IDEAS

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    1. Linjun Tang & Zhangong Zhou, 2015. "Weighted local linear CQR for varying-coefficient models with missing covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(3), pages 583-604, September.
    2. Zhao, Zhibiao & Xiao, Zhijie, 2014. "Efficient Regressions Via Optimally Combining Quantile Information," Econometric Theory, Cambridge University Press, vol. 30(6), pages 1272-1314, December.
    3. Ying Wei & Yanyuan Ma & Raymond J. Carroll, 2012. "Multiple imputation in quantile regression," Biometrika, Biometrika Trust, vol. 99(2), pages 423-438.
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    Cited by:

    1. Zhangong Zhou & Linjun Tang, 2019. "Testing for parametric component of partially linear models with missing covariates," Statistical Papers, Springer, vol. 60(3), pages 747-760, June.
    2. ChunJing Li & Yun Li & Xue Ding & XiaoGang Dong, 2020. "DGQR estimation for interval censored quantile regression with varying-coefficient models," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-17, November.
    3. Jing Sun, 2020. "An improvement on the efficiency of complete-case-analysis with nonignorable missing covariate data," Computational Statistics, Springer, vol. 35(4), pages 1621-1636, December.
    4. Shen, Yu & Liang, Han-Ying, 2018. "Quantile regression for partially linear varying-coefficient model with censoring indicators missing at random," Computational Statistics & Data Analysis, Elsevier, vol. 117(C), pages 1-18.

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