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Penalized spline estimator with multi smoothing parametersin bi-response multi-predictor nonparametric regression modelfor longitudinal data |
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| รหัสดีโอไอ | |
| Creator | 1. Anna Islamiyati 2. Fatmawati 3. Nur Chamidah |
| Title | Penalized spline estimator with multi smoothing parametersin bi-response multi-predictor nonparametric regression modelfor longitudinal data |
| Publisher | Research and Development Office, Prince of Songkla University |
| Publication Year | 2563 |
| Journal Title | Songklanakarin Journal of Science and Technology |
| Journal Vol. | 42 |
| Journal No. | 4 |
| Page no. | 897-909 |
| Keyword | penalized spline estimator, multi-smoothing parameters, longitudinal data, blood glucose levels, type 2 diabetespatients |
| URL Website | https://rdo.psu.ac.th/sjstweb/index.php |
| ISSN | 0125-3395 |
| Abstract | Penalized spline estimators that depend on a smoothing parameter is one type of estimator used in the estimationregression curve in nonparametric regression. The smoothing parameter is one of the most important components in the penalizedspline estimator because it is related to the smoothness of the regression curve. In this paper, we determine the optimum numberof smoothing parameters in a bi-response multi-predictor nonparametric regression model. Based on the result of the simulationstudy, we find that the optimum number of smoothing parameters corresponds to the number of predictor variables in eachresponse. We also apply the estimated model to case of blood glucose levels in type 2 diabetes patients. The results of study showthat there are different patterns of changes in blood glucose levels, both day and night, based on the length of care, the caloriediet, and the carbohydrate diet. |
