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A general result on the uniform in bandwidth consistency of kernel-type function estimators

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  • David Mason
  • Jan Swanepoel

Abstract

We develop a general theorem to prove the uniform in bandwidth consistency of kernel-type function estimators. This method unifies the approaches in some other recent papers. We show how to apply our results to kernel distribution function estimators and the smoothed empirical process. The results are applicable to establish strong uniform consistency of data-driven bandwidth kernel-type function estimators. Copyright Sociedad de Estadística e Investigación Operativa 2011

Suggested Citation

  • David Mason & Jan Swanepoel, 2011. "A general result on the uniform in bandwidth consistency of kernel-type function estimators," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(1), pages 72-94, May.
    • Handle: RePEc:spr:testjl:v:20:y:2011:i:1:p:72-94
    DOI: 10.1007/s11749-010-0188-0
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    References listed on IDEAS

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    1. D. Boos, 1986. "Rates of convergence for the distance between distribution function estimators," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 33(1), pages 197-202, December.
    2. Jan W. H. Swanepoel & Francois C. Van Graan, 2005. "A New Kernel Distribution Function Estimator Based on a Non‐parametric Transformation of the Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 32(4), pages 551-562, December.
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    Cited by:

    1. David Mason, 2012. "Proving consistency of non-standard kernel estimators," Statistical Inference for Stochastic Processes, Springer, vol. 15(2), pages 151-176, July.
    2. Salim Bouzebda & Thouria El-hadjali & Anouar Abdeldjaoued Ferfache, 2023. "Uniform in Bandwidth Consistency of Conditional U-statistics Adaptive to Intrinsic Dimension in Presence of Censored Data," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(2), pages 1548-1606, August.
    3. Paul Deheuvels & Sarah Ouadah, 2013. "Uniform-in-Bandwidth Functional Limit Laws," Journal of Theoretical Probability, Springer, vol. 26(3), pages 697-721, September.
    4. Bouzebda, Salim & Elhattab, Issam & Seck, Cheikh Tidiane, 2018. "Uniform in bandwidth consistency of nonparametric regression based on copula representation," Statistics & Probability Letters, Elsevier, vol. 137(C), pages 173-182.

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