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Simultaneous Error Bars

  • Wolfgang Härdle
Part of the Springer Series in Statistics book series (SSS)

Abstract

In Section 5.1.1 we mentioned a basic technique to compute asymptotic confidence intervals for m(x). However, this technique ignores the bias of the Nadaraya-Watson estimate and employs plug-in estimation of f(x) and σ2(x). In this section we present a bootstrap technique which does not need explicit estimation of functional of f, σ2, or m. The bootstrap is a resampling technique that prescribes taking “bootstrap samples» using the same random mechanism that generated the data. A bootstrap procedure automatically incorporating the bias term is the so called golden section bootstrap, introduced by Härdle and Mammen (1988).

Keywords

Confidence Limit Bootstrap Sample Coverage Probability Simultaneous Confidence Interval Bootstrap Residual 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York Inc. 1991

Authors and Affiliations

  • Wolfgang Härdle
    • 1
  1. 1.Center for Operations Research and EconometricsUniversité Catholique de LouvainLouvain-La-NeuveBelgium

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