Estimasi Densitas Mulus dengan Metode Kernel (Kernel Method in Smooth Density Estimation)

Abstract

Let i = 1,2,…,n be independent observation data from a distribution with an unknown density function f . The function f could be estimated by parametric and nonparametric approach. In nonparametric approach, the function f is assumed to be a smooth function or quadratic integrable function, so the function f could be estimated by kernel estimator. The smoothing level of kernel estimator depends to the smoothing parameter. The big smoothing parameter gives a estimation function which over smooth and the contrary. Key words : smooth density, kernel estimator.