JURNAL SISTEM KOMPUTER
Vol 1, No 1 (2011): Sistem dan Aplikasi Komputer

Comparation on Several Smoothing Methods in Nonparametric Regression

Isnanto, Rizal (Unknown)



Article Info

Publish Date
23 Mar 2011

Abstract

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-andLower Smoothing are also explained deeply, related to Lowess and Loess. Finally, the Kernel Smoothing Method involves three methods discussed. These are NadarayaWatson 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.Index Terms — nonparametric regression, smoothing, moving average, estimator, curve construction.

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