A Comparison of the Nonparametric Regression Models using Smoothing Spline and Kernel Regression

Aydin D.

Conference of the World-Academy-of-Science-Engineering-and-Technology, Bangkok, Thailand, 14 - 16 December 2007, vol.26, pp.730-734 identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 26
  • City: Bangkok
  • Country: Thailand
  • Page Numbers: pp.730-734
  • Keywords: Kernel regression, Nonparametric models, Prediction, Smoothing spline
  • Anadolu University Affiliated: No


This paper study about using of nonparametric models for Gross National Product data in Turkey and Stanford heart transplant data. It is discussed two nonparametric techniques called smoothing spline and kernel regression. The main goal is to compare the techniques used for prediction of the nonparametric regression models. According to the results of numerical studies, it is concluded that smoothing spline regression estimators are better than those of the kernel regression.