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Universal Consistency of Local Polynomial Kernel Regression Estimates

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  • Michael Kohler

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  • Michael Kohler, 2002. "Universal Consistency of Local Polynomial Kernel Regression Estimates," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 54(4), pages 879-899, December.
    • Handle: RePEc:spr:aistmt:v:54:y:2002:i:4:p:879-899
    DOI: 10.1023/A:1022427805425
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    References listed on IDEAS

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    1. Kohler, Michael, 1999. "Universally Consistent Regression Function Estimation Using Hierarchial B-Splines," Journal of Multivariate Analysis, Elsevier, vol. 68(1), pages 138-164, January.
    2. Györfi L. & Kohler M. & Walk H., 1998. "Weak And Strong Universal Consistency Of Semi-Recursive Kernel And Partitioning Regression Estimates," Statistics & Risk Modeling, De Gruyter, vol. 16(1), pages 1-18, January.
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    Citations

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    Cited by:

    1. Sheng, Baohuai & Zhu, Hancan, 2018. "The convergence rate of semi-supervised regression with quadratic loss," Applied Mathematics and Computation, Elsevier, vol. 321(C), pages 11-24.
    2. Ahnaf Rafi, 2023. "Efficient Semiparametric Estimation of Average Treatment Effects Under Covariate Adaptive Randomization," Papers 2305.08340, arXiv.org.
    3. Kohler, Michael & Krzyzak, Adam, 2007. "Asymptotic confidence intervals for Poisson regression," Journal of Multivariate Analysis, Elsevier, vol. 98(5), pages 1072-1094, May.
    4. Baranyi, Máté & Bolla, Marianna, 2021. "Iterated conditional expectation algorithm on DAGs and regression graphs," Econometrics and Statistics, Elsevier, vol. 20(C), pages 131-152.

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