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.
Recommended Citation
Härdle, Wolfgang and Linton, Oliver B., "Applied Nonparametric Methods" (1994). Cowles Foundation Discussion Papers. 1312.
https://elischolar.library.yale.edu/cowles-discussion-paper-series/1312