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

Rahmat Hidayat, I. Nyoman Budiantara*, Bambang W. Otok, Vita Ratnasari

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)3942-3953
Number of pages12
JournalCommunications in Statistics - Theory and Methods
Volume50
Issue number17
DOIs
Publication statusPublished - 2021

Keywords

  • Kernel
  • Non parametric regression
  • PLS
  • Spline

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