MULTIVARIATE NONPARAMETRIC KERNEL ESTIMATION

摘要

This paper is focused on multivariate estimation of density and distribution function by nonparametric kernel approach. The main goal is to describe univariate and multivariate nonparametric kernel estimation using selected kernel functions and smoothing parameters including a real application. The influence of basic parameters on the resulting models and proposed optimization methods are also analysed for further models of use (e.g. in reliability theory).