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, Tayland, 14 - 16 Aralık 2007, cilt.26, ss.730-734 identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 26
  • Basıldığı Şehir: Bangkok
  • Basıldığı Ülke: Tayland
  • Sayfa Sayıları: ss.730-734
  • Anahtar Kelimeler: Kernel regression, Nonparametric models, Prediction, Smoothing spline
  • Anadolu Üniversitesi Adresli: Hayır

Özet

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.