On Inference of Overlapping Coefficients in Two Inverse Lomax Populations
Methodology
2019-10-08 v1
Abstract
Overlapping coefficient is a direct measure of similarity between two distributions which is recently becoming very useful. This paper investigates estimation for some well-known measures of overlap, namely Matusita's measure , Weitzman's measure and based on Kullback-Leibler. Two estimation methods considered in this study are point estimation and Bayesian approach. Two Inverse Lomax populations with different shape parameters are considered. The bias and mean square error properties of the estimators are studied through a simulation study and a real data example.
Keywords
Cite
@article{arxiv.1910.02542,
title = {On Inference of Overlapping Coefficients in Two Inverse Lomax Populations},
author = {Hamza Dhaker and El Hadji Deme and Salah El-Adlouni},
journal= {arXiv preprint arXiv:1910.02542},
year = {2019}
}