On Inference of Overlapping Coefficients in Two Inverse Lomax Populations

Autor: Hamza Dhaker, El Hadji Deme, Salah El-Adlouni
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Journal of Statistical Theory and Applications (JSTA), Vol 20, Iss 1 (2021)
Druh dokumentu: article
ISSN: 2214-1766
DOI: 10.2991/jsta.d.210107.002
Popis: 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 ρ, Weitzman's measure Δ and Λ 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.
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