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Asymptotic Certainty Bands for Kernel Density Estimators Based upon a Bootstrap Resampling Scheme

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Statistical Models and Methods for Biomedical and Technical Systems

Part of the book series: Statistics for Industry and Technology ((SIT))

Abstract

In this chapter, we show that a single bootstrap suffices to construct sharp uniform asymptotic certainty (or asymptotically almost sure confidence) bands for nonparametric kernel-type density estimators.

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Author information

Authors and Affiliations

  1. LSTA, Université Paris VI, Bourg-la-Reine, France

    Paul Deheuvels

  2. Sanofi-Aventis Recherche, Montpellier, France

    Gérard Derzko

Authors
  1. Paul Deheuvels
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  2. Gérard Derzko
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Editor information

Editors and Affiliations

  1. Department of Mathematics and Statistics, University of Cyprus, CY-1678, Nicosia, Cyprus

    Filia Vonta

  2. UFR Sciences et Modélisation, Université Victor Segalen Bordeaux 2, 33076, Bordeaux Cedex, France

    Mikhail Nikulin

  3. Laboratoire de Mathématiques Appliquées, Université de Technologie de Compiègne, 60205, Compiègne Cedex, France

    Nikolaos Limnios

  4. Université Paris V, 45 rue des Saints-Pères, 75270, Paris Cedex 06, France

    Catherine Huber-Carol

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© 2008 Birkhäuser Boston

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Deheuvels, P., Derzko, G. (2008). Asymptotic Certainty Bands for Kernel Density Estimators Based upon a Bootstrap Resampling Scheme. In: Vonta, F., Nikulin, M., Limnios, N., Huber-Carol, C. (eds) Statistical Models and Methods for Biomedical and Technical Systems. Statistics for Industry and Technology. Birkhäuser Boston. https://doi.org/10.1007/978-0-8176-4619-6_13

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