A versatile family of distributions: Log-linear regression model and applications to real data

This article introduces a tractable generator for constructing flexible families of continuous distributions called the exponent-G-M (ExpG-M). Properties of the defined models generator are studied such as moments, mean deviation, moment of residual life, entropy, and order statistics. The ExpG-M mo...

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Format: Article
Language:English
Published: Elsevier 2025-04-01
Series:Kuwait Journal of Science
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Online Access:https://www.sciencedirect.com/science/article/pii/S230741082500029X
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collection DOAJ
description This article introduces a tractable generator for constructing flexible families of continuous distributions called the exponent-G-M (ExpG-M). Properties of the defined models generator are studied such as moments, mean deviation, moment of residual life, entropy, and order statistics. The ExpG-M model's parameter was estimated using both maximum likelihood estimation (MLE) and Bayesian estimation (BE) methods with a square error loss function, also assessed through Monte Carlo simulation studies. A special member called exponent generalized exponential-exponential distribution (ExpGE-E) is discussed; a related log-regression model based on ExpGE-E is introduced. Applications of the ExpGE-E and its regression model to real-life datasets shows that the proposed models have better modeling abilities than many competing distributions. © 2025 The Authors
format Article
id doaj-art-bdeed08615cc4b20a8b8a1db4eeff73c
institution Kabale University
issn 2307-4108
2307-4116
language English
publishDate 2025-04-01
publisher Elsevier
record_format Article
series Kuwait Journal of Science
spelling doaj-art-bdeed08615cc4b20a8b8a1db4eeff73c2025-08-20T03:47:21ZengElsevierKuwait Journal of Science2307-41082307-41162025-04-0152210038510.1016/j.kjs.2025.100385A versatile family of distributions: Log-linear regression model and applications to real dataThis article introduces a tractable generator for constructing flexible families of continuous distributions called the exponent-G-M (ExpG-M). Properties of the defined models generator are studied such as moments, mean deviation, moment of residual life, entropy, and order statistics. The ExpG-M model's parameter was estimated using both maximum likelihood estimation (MLE) and Bayesian estimation (BE) methods with a square error loss function, also assessed through Monte Carlo simulation studies. A special member called exponent generalized exponential-exponential distribution (ExpGE-E) is discussed; a related log-regression model based on ExpGE-E is introduced. Applications of the ExpGE-E and its regression model to real-life datasets shows that the proposed models have better modeling abilities than many competing distributions. © 2025 The Authorshttps://www.sciencedirect.com/science/article/pii/S230741082500029Xbayes estimationentropylog-regression modelmaximum likelihood estimationmomentssimulationt-x families
spellingShingle A versatile family of distributions: Log-linear regression model and applications to real data
Kuwait Journal of Science
bayes estimation
entropy
log-regression model
maximum likelihood estimation
moments
simulation
t-x families
title A versatile family of distributions: Log-linear regression model and applications to real data
title_full A versatile family of distributions: Log-linear regression model and applications to real data
title_fullStr A versatile family of distributions: Log-linear regression model and applications to real data
title_full_unstemmed A versatile family of distributions: Log-linear regression model and applications to real data
title_short A versatile family of distributions: Log-linear regression model and applications to real data
title_sort versatile family of distributions log linear regression model and applications to real data
topic bayes estimation
entropy
log-regression model
maximum likelihood estimation
moments
simulation
t-x families
url https://www.sciencedirect.com/science/article/pii/S230741082500029X