Spline Estimator for Bi-Responses and Multi-Predictors Nonparametric Regression Model in Case of Longitudinal Data
Adji Achmad Rinaldo Fernandes, I Nyoman Budiantara, Bambang Widjanarko Otok and Suhartono
DOI : 10.3844/jmssp.2015.61.69
Journal of Mathematics and Statistics
Volume 11, Issue 2
Nonparametric regression approach is used when the shape of the curve regression is unknown. The spline estimator approach for longitudinal data can accommodate the correlation between observations within the same subject, which is not found in the cross-section data, so that the autocorrelation assumption problem can be resolved. On the other hand, with bi-responses approach, it will accommodate any correlation between each response variables. The purposes of this study are (1) to obtain the function form of the nonparametric bi-responses and multi-predictorsregression on longitudinal data, (2) to obtain the spline estimator in estimating the nonparametric bi-responses and multi-predictorsregression curve on longitudinal data and (3) to apply the spline estimator in estimating the curve of nonparametric bi-responses and multi-predictorsregression on longitudinal data. Bi-responses and multi-predictors nonparametric regression of the spline estimator on longitudinal data which meet the criteria of minimizing Penalized Weighted Least Square (PWLS). Application of data set (Patient in Pulmonary Tuberculosis) result shows that the spline estimator can be applied which gives the value of R2 of 97.77%.
© 2015 Adji Achmad Rinaldo Fernandes, I Nyoman Budiantara, Bambang Widjanarko Otok and Suhartono . This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.