The regression curve estimation by using mixed smoothing spline and kernel (MsS-K) model. Issue 17 (9th August 2021)

• Record Type: Journal Article
• Authors: Hidayat, Rahmat; Budiantara, I. Nyoman; Otok, Bambang W.; Ratnasari, Vita
• Is Part Of: Communications in statistics. Volume 50:Issue 17(2021)
• Page Start: 3942
• Page End: 3953
• Publication Date: 2021-08-09
• Subjects: Non parametric regression -- Spline -- Kernel -- PLS; 62G08; Mathematical statistics -- Periodicals; Mathematics; Statistics; 519.2
• DOI: 10.1080/03610926.2019.1710201
• Languages: English
• ISSNs: 0361-0926

Abstract

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.