Applied Nonparametric Methods
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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|Date of creation:||1992|
|Contact details of provider:|| Postal: TILBURG UNIVERSITY, CENTER FOR ECONOMIC RESEARCH, 5000 LE TILBURG THE NETHERLANDS.|
Phone: 31 13 4663050
Fax: 31 13 4663066
Web page: http://center.uvt.nl/
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- repec:cup:etheor:v:6:y:1990:i:4:p:466-79 is not listed on IDEAS
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