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Bandwidth selection procedures tor kernel density estimates
Authors:Steven Bean  Chris P Tsokos
Institution:1. Department of Mathematics , University of Central Florida , Orlando, FL;2. Department of Mathematics , University of South Florida , Tampa, FL
Abstract:A crucial problem in kernel density estimates of a probability density function is the selection of the bandwidth. The aim of this study is to propose a procedure for selecting both fixed and variable bandwidths. The present study also addresses the question of how different variable bandwidth kernel estimators perform in comparison with each other and to the fixed type of bandwidth estimators. The appropriate algorithms for implementation of the proposed method are given along with a numerical simulation.The numerical results serve as a guide to determine which bandwidth selection method is most appropriate for a given type of estimator over a vide class of probability density functions, Also, we obtain a numerical comparison of the different types of kernel estimators under various types of bandwidths.
Keywords:nonparametic density estimate  stabilized jackknifed maximum likelilhood  penalized maximum likelihood  goodness-of-fit criteria
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