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.

Original languageEnglish
Pages (from-to)3942-3953
Number of pages12
JournalCommunications in Statistics - Theory and Methods
Issue number17
Publication statusPublished - 2021


  • Kernel
  • Non parametric regression
  • PLS
  • Spline


Dive into the research topics of 'The regression curve estimation by using mixed smoothing spline and kernel (MsS-K) model'. Together they form a unique fingerprint.

Cite this