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A Review of Nonparametric Time Series Analysis


  • Wolfgang Härdle
  • Helmut Lütkepohl
  • Rong Chen


Various features of a given time series may be analyzed by nonparametric techniques. Generally the characteristic of interest is allowed to have a general form which is approximated increasingly precisely when the sample size goes to infinity. We review nonparametric methods of this type for estimating the spectral density, the conditional mean, higher order conditional moments or conditional densities. Moreover, density estimation with correlated data, bootstrap methods for time series and nonparametric trend analysis are described. Beaucoup des elements des séries temporelles sont analysable par des methodes non‐paramétriques. L'objet d'interé a une forme generale qui est approximće plus et plus préciseacute;ment le nomber d'obervations augmente. cet article présente un survey des procédures non paramétriques en analyse des séries temporelles. Nous illustroas au moyen d'exemples portant sur I'cstimation de densité, sur le bootstrap et l'estimation de tendence.

Suggested Citation

  • Wolfgang Härdle & Helmut Lütkepohl & Rong Chen, 1997. "A Review of Nonparametric Time Series Analysis," International Statistical Review, International Statistical Institute, vol. 65(1), pages 49-72, April.
  • Handle: RePEc:bla:istatr:v:65:y:1997:i:1:p:49-72
    DOI: 10.1111/j.1751-5823.1997.tb00367.x

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