The Estimation of Smoothing Parameter using Smoothing Techniques

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. Key Words : Smoothing Parameter; Smoothing Technique; Smoothing Spline; Kernel Regression; PenalizedSpline Regression