The Estimation of Smoothing Parameter using Smoothing Techniques

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DOI: https://doi.org/10.14456/sustj.2012.10
Keywords:
smoothing parameter smoothing technique smoothing spline kernel regression penalized spline regression

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Autcha Araveeporn
Department of Applied Statistics, Faculty of Science, King Monkut’s Institute of Technology Ladkrabang, Thailand. Corresponding author's e-mail:: kaautcha@kmitl.ac.th

Abstract

This article discusses on the smoothing parameter which is controlled by interpolating spline basedon the smoothing techniques that consisted of smoothing spline method, kernel regression method, andpenalized spline regression method.


The smoothing parameter is controlled the fitting model and the trade of between the bias of theestimator. We also propose the range of smoothing parameter of these methods to fit the smoothing functionwhich data is nonlinear. Therefore, we mention the characteristic of smoothing function when the smoothingparameters have the various values. According to the results, it is concluded that the smoothing parameterof the smoothing spline method is suitable worked between zero to one, the kernel regression is goodperformance between two to ten, and the penalized spline is useful between one to ten.

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How to Cite
Araveeporn, A. (2013). The Estimation of Smoothing Parameter using Smoothing Techniques. Science, Engineering and Health Studies, 6(1), 14–22. https://doi.org/10.14456/sustj.2012.10
Issue
Volume 6, Number 1 (January - June), 2012
Section
Review Articles

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