%0 Journal Article
%T Comparation on Several Smoothing Methods in Nonparametric Regression
%A Rizal Isnanto
%J Jurnal Sistem Komputer
%D 2011
%I Diponegoro University
%X There are three nonparametric regression methods covered in this section. These are Moving Average Filtering-Based Smoothing, Local Regression Smoothing, and Kernel Smoothing Methods. The Moving Average Filtering-Based Smoothing methods discussed here are Moving Average Filtering and Savitzky-Golay Filtering. While, the Local Regression Smoothing techniques involved here are Lowess and Loess. In this type of smoothing, Robust Smoothing and Upper-and-Lower Smoothing are also explained deeply, related to Lowess and Loess. Finally, the Kernel Smoothing Method involves three methods discussed. These are Nadaraya-Watson Estimator, Priestley-Chao Estimator, and Local Linear Kernel Estimator. The advantages of all above methods are discussed as well as the disadvantages of the methods.
%K nonparametric regression
%K smoothing
%K moving average
%K estimator
%K curve construction
%U http://jsiskom.undip.ac.id/index.php/jsk/article/view/6