Applied nonparametric methods
No 1992003, CORE Discussion Papers from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)
In this note we review different approaches to non parametric regression. Kernel estimators are motivated from local averaging, solving ill-posed problems and weighting of binned data. Kernel estimators are compared to k-NN estimators and splines. The choice of smoothing paramet.er is discussed and finally the method is applied for nonparametric prediction of time series.
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