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Strong universal consistency of smooth kernel regression estimates

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  • Harro Walk

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  • Harro Walk, 2005. "Strong universal consistency of smooth kernel regression estimates," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 57(4), pages 665-685, December.
    • Handle: RePEc:spr:aistmt:v:57:y:2005:i:4:p:665-685
    DOI: 10.1007/BF02915432
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    References listed on IDEAS

    as
    1. Miroslaw Pawlak, 1991. "On the almost everywhere properties of the kernel regression estimate," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(2), pages 311-326, June.
    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.
    3. Györfi, László & Walk, Harro, 1997. "On the strong universal consistency of a recursive regression estimate by Pál Révész," Statistics & Probability Letters, Elsevier, vol. 31(3), pages 177-183, January.
    4. Harro Walk, 2001. "Strong Universal Pointwise Consistency of Recursive Regression Estimates," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 53(4), pages 691-707, December.
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    Cited by:

    1. Györfi László & Walk Harro, 2013. "Rate of convergence of the density estimation of regression residual," Statistics & Risk Modeling, De Gruyter, vol. 30(1), pages 55-74, March.
    2. Györfi, László & Walk, Harro, 2012. "Strongly consistent density estimation of the regression residual," Statistics & Probability Letters, Elsevier, vol. 82(11), pages 1923-1929.
    3. Matthias Hansmann & Michael Kohler & Harro Walk, 2019. "On the strong universal consistency of local averaging regression estimates," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(5), pages 1233-1263, October.
    4. 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.
    5. Ahmed Ouazza & Noureddine Rhomari & Zoubir Zarrouk, 2022. "Kernel method to estimate nonlinear structural equation models," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(5), pages 3465-3480, October.
    6. Walk, Harro, 2010. "Strong consistency of kernel estimates of regression function under dependence," Statistics & Probability Letters, Elsevier, vol. 80(15-16), pages 1147-1156, August.

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