Friday, Oct 13, 2017 - 3:30pm - Allen 14
Using empirical likelihood estimation of density functionals to test location and scale parameters
Dr. Ningning Wang, Math&Stat,Jackson State University
Title: Using empirical likelihood estimation of density functionals to test location and scale parameters
Abstract: A novel class of empirical likelihood nonparametric estimates of density functionals (ELKDFE) is constructed based on kernel density function (KDF) and the concepts of empirical likelihood. These estimates have smaller bias and mean square error than the standard estimates based on KDF. Applications of this to location and scale parameters testing simulation results show that the empirical likelihood estimates are significantly better than the standard ones for small and moderate sample sizes.
Document: Dr. NingNing Wang.pdf