Comparison of Gaussian and Epancehnikov Kernels - Fadillah, Nur; Audina Dariah, Priliany; Anggraeni, Anisa; Cahyani, Nur; Handayani, Lilies (LPPM Universitas Tadulako, 2022)
Kernel regression is a nonparametric analysis with smoothing method. Smoothing has become synonymous with nonparametric methods used to estimate functions. The purpose of smoothing is to remove variability from data that has no effect so that the characteristics of the data will appear clear. Kernel regression has a flexible form and the mathematical calculations are easy to adjust. In kernel regression, an estimator is known which is usually used to estimate the regression function, namely the Nadaraya-Watson estimator. This study aims to show how to estimate data using nonparametric regression Gaussian and Eponocvh kernels with the Nadaraya-Watson estimator and the bandwidth selection methods are