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 …

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 in nity. 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 …