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Annals of Data Science

18-04-2024

Half Logistic Generalized Rayleigh Distribution for Modeling Hydrological Data

Authors: Adebisi A. Ogunde, Subhankar Dutta, Ehab M. Almetawally

Published in: Annals of Data Science

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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 \({\varvec{\delta}}\)-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.

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Title: Half Logistic Generalized Rayleigh Distribution for Modeling Hydrological Data
Authors: Adebisi A. Ogunde
Subhankar Dutta
Ehab M. Almetawally
Publication date: 18-04-2024
Publisher: Springer Berlin Heidelberg
Published in: Annals of Data Science
Print ISSN: 2198-5804
Electronic ISSN: 2198-5812
DOI: https://doi.org/10.1007/s40745-024-00527-2

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