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The regression curve estimation by using mixed smoothing spline and kernel (MsS-K) model

Author

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  • Rahmat Hidayat
  • I. Nyoman Budiantara
  • Bambang W. Otok
  • Vita Ratnasari

Abstract

In this article, we propose a new method in estimating non parametric regression curve. This method combines the smoothing Spline and Kernel functions. Estimation of the estimator is completed by minimizing penalized least square. To see the performance of the model, this model is applied to simulation data with a variety of sample sizes and error variances. Then, the model is applied to the Unemployment Rate data in East Java Province, Indonesia. The results show that this model provides good performance in modeling data and predictions.

Suggested Citation

  • Rahmat Hidayat & I. Nyoman Budiantara & Bambang W. Otok & Vita Ratnasari, 2021. "The regression curve estimation by using mixed smoothing spline and kernel (MsS-K) model," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 50(17), pages 3942-3953, August.
    • Handle: RePEc:taf:lstaxx:v:50:y:2021:i:17:p:3942-3953
    DOI: 10.1080/03610926.2019.1710201
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