Smoothing Parameter Selection for Nonparametric Regression Using Smoothing Spline

Authors

  • Dursun Aydin
  • Memmedaga Memmedli
  • Rabia Ece Omay

Abstract

In this paper, the smoothing parameter selection problem has been examined in respect to a smoothing spline implementation in predicting nonparametric regression models. For this purpose, a simulation study has been performed by using a program written in MATLAB. The simulation study provides a comparison of the nine smoothing parameter selection methods. In this connection, 500 replications have been performed in simulation for sample sets with different sizes. Thus, the appropriate selection criteria are provided for a suitable smoothing parameter selection.

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How to Cite

Aydin, D., Memmedli, M., & Omay, R. E. (2013). Smoothing Parameter Selection for Nonparametric Regression Using Smoothing Spline. European Journal of Pure and Applied Mathematics, 6(2), 222–238. Retrieved from https://www.ejpam.com/index.php/ejpam/article/view/1362