Yulianto, Tony and Kuzairi, Kuzairi and Azizah, Noer and Mardianto, M. Fariz Fadillah and Yudistira, Ira and Faisol, Faisol and Amalia, Rica (2023) THE PARAMETRIC AND NONPARAMETRIC ESTIMATOR IN SEMIPARAMETRIC REGRESSION FOR LONGITUDINAL DATA WITH SPLINE APPROACH. Jurnal Ilmiah Kursor, 11 (4). pp. 187-194. ISSN 2301-6914 (online) 0216-0544 (printed)
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2023_THE PARAMETRIC AND NONPARAMETRIC ESTIMATOR IN SEMIPARAMETRIC REGRESSION FOR LONGITUDINAL DATA WITH SPLINE APPROACH.pdf Download (482kB) |
Abstract
Regression analysis aims to determine the relationship between response variables and predictor variables. There are three approaches to estimate regression curves, there are parametric, nonparametric, and semiparametric regression. In this study, the form of spline semiparametric regression curve estimator for longitudinal data assessed. Based on the estimator that be obtained by using Weighted Least Square (WLS) optimization applied to model electricity consumption in Madura by choosing a model for longitudinal data based on linear spline estimator with two knot. The good criterion of the model is using the GCV value, the coefficient of determination and the value of MSE. The best model is a model that has a high coefficient of determination and a small MSE value. This spline model has a determination coefficient value of 99,72911% and MSE 32,50458.
| Item Type: | Article |
|---|---|
| Subjects: | Q Science > QA Mathematics |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Mathematics |
| Depositing User: | rica amalia |
| Date Deposited: | 29 May 2023 04:28 |
| Last Modified: | 29 May 2023 04:28 |
| URI: | http://repository.uim.ac.id/id/eprint/804 |
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