Title

Applied Nonparametric Methods

Document Type

Discussion Paper

Publication Date

3-1-1994

CFDP Number

1069

CFDP Pages

43

Abstract

We review different approaches to nonparametric density and regression estimation. Kernel estimators are motivated from local averaging and solving ill-posed problems. Kernel estimators are compared to k -NN estimators, orthogonal series and splines. Pointwise and uniform confidence bands are described, and the choice of smoothing parameter is discussed. Finally, the method is applied to nonparametric prediction of time series and to semiparametric estimation.

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