Estimator Nadaraya-Watson dengan Pendekatan Cross Validation dan Generalized Cross Validation untuk Mengestimasi Produksi Jagung

Febriolah Lamusu (Universitas Negeri Gorontalo)
Tedy Machmud (Universitas Negeri Gorontalo)
Resmawan Resmawan (Universitas Negeri Gorontalo)

Indonesian Journal of Applied Statistics
Vol 3, No 2 (2020)

Nadaraya-Watson Estimator with kernel approach depends on two-parameter, those are kernel function and bandwidth choice. However, between the two of them, bandwidth choice gave a huge impact on the result of the estimation. By minimizing the value of Mean Square Error (MSE), Cross-Validation (CV) and Generalized Cross-Validation (GCV) gave the optimal bandwidth value. In this research, corn production was considered as the dependent variable, while the planted area, harvested area, and the fertilizer as the independent variable. The result of this research showed that Nadaraya-Watson Estimator with Generalized Cross-Validation gives a better corn production estimation with optimal bandwidth value 742392,2, with and  with MSE 202583,9.Keywords: kernel, estimator Nadaraya-Watson, cross validation, generalized cross validation.