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Bootstrap Bandwidth Selection in Kernel Density Estimation from a Contaminated Sample

Author

Listed:
  • Delaigle, A.
  • Gijbels, I.

Abstract

In this paper we consider kernel estimation of a density when the data are contaminated by random noise. More specifically we deal with the problem of how to choose the bandwidth parameter in practice.

Suggested Citation

  • Delaigle, A. & Gijbels, I., 2001. "Bootstrap Bandwidth Selection in Kernel Density Estimation from a Contaminated Sample," Papers 0116, Catholique de Louvain - Institut de statistique.
    • Handle: RePEc:fth:louvis:0116
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    Cited by:

    1. Bissantz, Nicolai & Dümbgen, Lutz & Holzmann, Hajo & Munk, Axel, 2007. "Nonparametric confidence bands in deconvolution density estimation," Technical Reports 2007,03, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.

    More about this item

    Keywords

    EVALUATION ; BANDWIDTH ; BOOTSTRAP;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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