Applied Nonparametric Methods

Wolfgang Härdle and Oliver Linton

No 1069, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

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.

Pages: 43 pages
Date: 1994-03
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Citations: View citations in EconPapers (286)

Published in D.F. McFadden and R.F. Engle (eds.), The Handbook of Econometrics, Vol. IV, North Holland, 1994, pp. 2295-2339

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Chapter: Applied nonparametric methods (1986)
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