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arXiv · 1910.02542

On Inference of Overlapping Coefficients in Two Inverse Lomax Populations

Hamza Dhaker·El Hadji Deme·Salah El-Adlouni
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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 $\rho$, Weitzman's measure $\Delta$ and $\Lambda$ 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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Hamza Dhaker, El Hadji Deme, Salah El-Adlouni. 2019-10-06. On Inference of Overlapping Coefficients in Two Inverse Lomax Populations. https://arxiv.org/abs/1910.02542

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