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 language | English |
|---|---|
| Pages (from-to) | 3942-3953 |
| Number of pages | 12 |
| Journal | Communications in Statistics - Theory and Methods |
| Volume | 50 |
| Issue number | 17 |
| DOIs | |
| Publication status | Published - 2021 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
Keywords
- Kernel
- Non parametric regression
- PLS
- Spline
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