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Strong Universal Pointwise Consistency of Recursive Regression Estimates

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  • Harro Walk

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  • 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.
    • Handle: RePEc:spr:aistmt:v:53:y:2001:i:4:p:691-707
    DOI: 10.1023/A:1014692616736
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    References listed on IDEAS

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    1. Algoet, Paul & Györfi, László, 1999. "Strong Universal Pointwise Consistency of Some Regression Function Estimates," Journal of Multivariate Analysis, Elsevier, vol. 71(1), pages 125-144, October.
    2. Greblicki, Wlodzimierz & Pawlak, Miroslaw, 1987. "Necessary and sufficient consistency conditions for a recursive kernel regression estimate," Journal of Multivariate Analysis, Elsevier, vol. 23(1), pages 67-76, October.
    3. 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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    Cited by:

    1. 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.
    2. Kohler, Michael & Krzyzak, Adam, 2007. "Asymptotic confidence intervals for Poisson regression," Journal of Multivariate Analysis, Elsevier, vol. 98(5), pages 1072-1094, May.
    3. Aboubacar Amiri, 2013. "Asymptotic normality of recursive estimators under strong mixing conditions," Statistical Inference for Stochastic Processes, Springer, vol. 16(2), pages 81-96, July.
    4. Salah, Khardani & Yousri, Slaoui, 2019. "Nonparametric relative regression under random censorship model," Statistics & Probability Letters, Elsevier, vol. 151(C), pages 116-122.
    5. Vidal-Sanz, Jose M., 2004. "Pointwise universal consistency of nonparametric linear estimators," DEE - Working Papers. Business Economics. WB wb045821, Universidad Carlos III de Madrid. Departamento de Economía de la Empresa.
    6. Matthias Hansmann & Benjamin M. Horn & Michael Kohler & Stefan Ulbrich, 2022. "Estimation of conditional distribution functions from data with additional errors applied to shape optimization," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(3), pages 323-343, April.
    7. 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.
    8. Walk, Harro, 2008. "A universal strong law of large numbers for conditional expectations via nearest neighbors," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1035-1050, July.

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