Dursun Aydin
A Comparison of the Nonparametric Regression Models using Smoothing Spline and Kernel Regression
588 - 592
2007
1
12
International Journal of Mathematical and Computational Sciences
https://publications.waset.org/pdf/4537
https://publications.waset.org/vol/12
World Academy of Science, Engineering and Technology
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.
Open Science Index 12, 2007