Kernel-Spline Estimation of Additive Nonparametric Regression Model

In this paper, we model the open unemployment rate with the Kernel-Spline model. We investigate and compare the performance of model Kernel-Spline by varying the Kernel function. The performance model has been compared with five Kernel function i.e. Kernel functions Uniform, Epanechnikov, Quartic, Gaussian, and Triweight. For these models, we conducted a comparison based on actual data sets, the unemployment rate in East Java. The best model was chosen based on the Generalized Cross Validation value and the coefficient of determination criteria. The empirical results obtained have shown that Spline-Kernel model by using the Gaussian Kernel better than other models.