METHODS OF BANDWITH SELECTION IN KERNNEL DENSITY ESTIMATION

ABSTRACT

In nonparametric density estimation processes, kernel density estimation is a commonly utilized tool. Kernel function selection and bandwidth selection are two crucial kernel density estimation approaches. In this study the Silverman’s rule method, Sheather-Jones method and Scott’s rule method of bandwidth selection was considered in implementing the selection procedure in choosing the bandwidth using the R statistical package.