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Order-Preserving Nonparametric Regression, With Applications to Conditional Distribution and Quantile Function Estimation

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  • Hall, Peter
  • Muller, Hans-Georg

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  • Hall, Peter & Muller, Hans-Georg, 2003. "Order-Preserving Nonparametric Regression, With Applications to Conditional Distribution and Quantile Function Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 598-608, January.
    • Handle: RePEc:bes:jnlasa:v:98:y:2003:p:598-608
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    Cited by:

    1. Samantha Leorato & Franco Peracchi, 2015. "Comparing Distribution and Quantile Regression," EIEF Working Papers Series 1511, Einaudi Institute for Economics and Finance (EIEF), revised Oct 2015.
    2. Abdelaati Daouia & Byeong U. Park, 2013. "On Projection-type Estimators of Multivariate Isotonic Functions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(2), pages 363-386, June.
    3. Hans-Georg Müller & Ying Zhang, 2005. "Time-Varying Functional Regression for Predicting Remaining Lifetime Distributions from Longitudinal Trajectories," Biometrics, The International Biometric Society, vol. 61(4), pages 1064-1075, December.
    4. Franco Peracchi & Samantha Leorato, 2015. "Shape Regressions," Working Papers gueconwpa~15-15-06, Georgetown University, Department of Economics.
    5. Shin, Yei Eun & Zhou, Lan & Ding, Yu, 2022. "Joint estimation of monotone curves via functional principal component analysis," Computational Statistics & Data Analysis, Elsevier, vol. 166(C).
    6. Colin Wu & Xin Tian & Jarvis Yu, 2010. "Nonparametric estimation for time-varying transformation models with longitudinal data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(2), pages 133-147.
    7. Rockafellar, R.T. & Royset, J.O. & Miranda, S.I., 2014. "Superquantile regression with applications to buffered reliability, uncertainty quantification, and conditional value-at-risk," European Journal of Operational Research, Elsevier, vol. 234(1), pages 140-154.
    8. Yuanhua Feng & Wolfgang Karl Härdle, 2021. "Uni- and multivariate extensions of the sinh-arcsinh normal distribution applied to distributional regression," Working Papers CIE 142, Paderborn University, CIE Center for International Economics.

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