Journal article

Improved density and distribution function estimation

V Oryshchenko, RJ Smith

Electronic Journal of Statistics | Institute of Mathematical Statistics | Published : 2019

Abstract

Given additional distributional information in the form of moment restrictions, kernel density and distribution function estimators with implied generalised empirical likelihood probabilities as weights achieve a reduction in variance due to the systematic use of this extra information. The particular interest here is the estimation of the density or distribution functions of (generalised) residuals in semi-parametric models defined by a finite number of moment restrictions. Such estimates are of great practical interest, being potentially of use for diagnostic purposes, including tests of parametric assumptions on an error distribution, goodness-of-fit tests or tests of overidentifying mome..

View full abstract

University of Melbourne Researchers