Half Logistic Generalized Rayleigh Distribution for Modeling Hydrological Data

Adebisi A. Ogunde (), Subhankar Dutta () and Ehab M. Almetawally ()
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Adebisi A. Ogunde: University of Ibadan
Subhankar Dutta: Vellore Institute of Technology, Chennai Campus
Ehab M. Almetawally: Delta University for Science and Technology

Annals of Data Science, 2025, vol. 12, issue 2, No 11, 667-694

Abstract: Abstract This article introduced a three-parameter extension of the Generalized Rayleigh distribution called half-logistic Generalized Rayleigh distribution, which has submodels the Generalized Rayleigh and Rayleigh distribution. The proposed model is quite flexible and adaptable to model any kind of life-time data. Its probability density function may sometimes be unimodal and its corresponding hazard rate may be of monotone or non-monotone shape. Standard statistical properties such as it ordinary and incomplete moments, quantile function, moment generating function, reliability function, stochastic ordering, order statistics, Renyi, and $${\varvec{\delta}}$$ δ -entropy are obtained. The maximum likelihood method is used to obtain the estimates of the model parameters. Two practical examples of hydrological data sets are presented.

Keywords: Maximum likelihood estimation; Monte Carlo simulation; $${\varvec{\delta}}$$ δ -entropy; Half-logistic generalized Rayleigh distribution (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s40745-024-00527-2

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