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A nonparametric approach for quantile regression

Author

Listed:
  • Mei Ling Huang

    (Department of Mathematics & Statistics, Brock University)

  • Christine Nguyen

    (Apotex Inc.)

Abstract

Quantile regression estimates conditional quantiles and has wide applications in the real world. Estimating high conditional quantiles is an important problem. The regular quantile regression (QR) method often designs a linear or non-linear model, then estimates the coefficients to obtain the estimated conditional quantiles. This approach may be restricted by the linear model setting. To overcome this problem, this paper proposes a direct nonparametric quantile regression method with five-step algorithm. Monte Carlo simulations show good efficiency for the proposed direct QR estimator relative to the regular QR estimator. The paper also investigates two real-world examples of applications by using the proposed method. Studies of the simulations and the examples illustrate that the proposed direct nonparametric quantile regression model fits the data set better than the regular quantile regression method.

Suggested Citation

  • Mei Ling Huang & Christine Nguyen, 2018. "A nonparametric approach for quantile regression," Journal of Statistical Distributions and Applications, Springer, vol. 5(1), pages 1-14, December.
    • Handle: RePEc:spr:jstada:v:5:y:2018:i:1:d:10.1186_s40488-018-0084-9
    DOI: 10.1186/s40488-018-0084-9
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    References listed on IDEAS

    as
    1. Huixia Judy Wang & Deyuan Li, 2013. "Estimation of Extreme Conditional Quantiles Through Power Transformation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(503), pages 1062-1074, September.
    2. Mei Ling Huang & Christine Nguyen, 2017. "High quantile regression for extreme events," Journal of Statistical Distributions and Applications, Springer, vol. 4(1), pages 1-20, December.
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    Cited by:

    1. Li Chen & Bin Jiang & Chuan Wang, 2023. "Climate change and urban total factor productivity: evidence from capital cities and municipalities in China," Empirical Economics, Springer, vol. 65(1), pages 401-441, July.

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