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

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.

Keywords:

• Non parametric regression
• Spline
• Kernel
• PLS

MATHEMATICS SUBJECT CLASSIFICATION:

• 62G08

Acknowledgment

Thanks to Direktorat Jendral Sumber Daya IPTEK dan DIKTI, Kemristekdikti, in collaboration with Lembaga Pengelola Dana Pendidikan (LPDP), which give the Beasiswa Unggulan Dosen Indonesia (BUDI) as a funder of this research.

Data availability

The data that support the findings of this study are available in in the BPS of East Java repository (https://jatim.bps.go.id).

Conflict of interest

The authors declare that there are no conflicts of interest regarding the publication of this paper.