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Quantile regression with doubly censored data

Author

Listed:
  • Lin, Guixian
  • He, Xuming
  • Portnoy, Stephen

Abstract

Quantile regression offers a semiparametric approach to modeling data with possible heterogeneity. It is particularly attractive for censored responses, where the conditional mean functions are unidentifiable without parametric assumptions on the distributions. A new algorithm is proposed to estimate the regression quantile process when the response variable is subject to double censoring. The algorithm distributes the probability mass of each censored point to its left or right appropriately, and iterates towards self-consistent solutions. Numerical results on simulated data and an unemployment duration study are given to demonstrate the merits of the proposed method.

Suggested Citation

  • Lin, Guixian & He, Xuming & Portnoy, Stephen, 2012. "Quantile regression with doubly censored data," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 797-812.
  • Handle: RePEc:eee:csdana:v:56:y:2012:i:4:p:797-812
    DOI: 10.1016/j.csda.2011.03.009
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Polpo, A. & de Campos, C.P. & Sinha, D. & Lipsitz, S. & Lin, J., 2014. "Transform both sides model: A parametric approach," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 903-913.
    2. repec:eee:csdana:v:113:y:2017:i:c:p:53-63 is not listed on IDEAS
    3. Niknam, Taher & Azizipanah-Abarghooee, Rasoul & Narimani, Mohammad Rasoul, 2012. "Reserve constrained dynamic optimal power flow subject to valve-point effects, prohibited zones and multi-fuel constraints," Energy, Elsevier, vol. 47(1), pages 451-464.
    4. repec:eee:jeborg:v:137:y:2017:i:c:p:113-131 is not listed on IDEAS
    5. repec:bla:istatr:v:84:y:2016:i:3:p:327-344 is not listed on IDEAS
    6. Portnoy, Stephen, 2014. "The jackknife’s edge: Inference for censored regression quantiles," Computational Statistics & Data Analysis, Elsevier, vol. 72(C), pages 273-281.
    7. Jakob W. Messner & Achim Zeileis & Jochen Broecker & Georg J. Mayr, 2013. "Improved Probabilistic Wind Power Forecasts with an Inverse Power Curve Transformation and Censored Regression," Working Papers 2013-01, Faculty of Economics and Statistics, University of Innsbruck.

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