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A weighted M-estimator for linear regression models with randomly truncated data

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  • Du, Jiang
  • Zhang, Zhongzhan
  • Xie, Tianfa

Abstract

This paper considers M-estimation for randomly truncated data. We propose a new estimation for left truncated data, and establish the sample properties of the proposed estimator. Finite sample performance of the proposed estimator is investigated via simulation studies.

Suggested Citation

  • Du, Jiang & Zhang, Zhongzhan & Xie, Tianfa, 2018. "A weighted M-estimator for linear regression models with randomly truncated data," Statistics & Probability Letters, Elsevier, vol. 138(C), pages 90-94.
    • Handle: RePEc:eee:stapro:v:138:y:2018:i:c:p:90-94
    DOI: 10.1016/j.spl.2018.02.055
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    References listed on IDEAS

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    1. Elias Ould-Saïd & Mohamed Lemdani, 2006. "Asymptotic Properties of a Nonparametric Regression Function Estimator with Randomly Truncated Data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 58(2), pages 357-378, June.
    2. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731, September.
    3. Arcones, Miguel A., 1996. "The Bahadur-Kiefer Representation of Lp Regression Estimators," Econometric Theory, Cambridge University Press, vol. 12(2), pages 257-283, June.
    4. Pollard, David, 1991. "Asymptotics for Least Absolute Deviation Regression Estimators," Econometric Theory, Cambridge University Press, vol. 7(2), pages 186-199, June.
    5. Zhou, Weihua, 2011. "A weighted quantile regression for randomly truncated data," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 554-566, January.
    6. Zeckhauser, Richard & Thompson, Mark, 1970. "Linear Regression with Non-Normal Error Terms," The Review of Economics and Statistics, MIT Press, vol. 52(3), pages 280-286, August.
    7. Frumento, Paolo & Bottai, Matteo, 2017. "An estimating equation for censored and truncated quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 113(C), pages 53-63.
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