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Research Article | Open Access

The modified Muth distribution: Statistical properties, entropy measures, and parameter estimation

H. M. Barakat1H. S. Bakouch2Mohamed A. Abd Elgawad3( )Hatem Semary3M. A. Alawady1,4I. A. Husseiny1M. G. Enany5T. S. Taher1
Department of Mathematics, Faculty of Science, Zagazig University, Zagazig 44519, Egypt
Department of Mathematics, Faculty of Science, Tanta University, Tanta, Egypt
Department of Mathematics and Statistics, Faculty of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia
Department of Statistics and Operations Research, College of Science, Qassim University, Buraydah 51482, Saudi Arabia
Faculty of Computers and Information Systems, Egyptian Chinese University, Cairo 11528, Egypt
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Abstract

In this study, the modified Muth distribution was introduced as a parsimonious lifetime model obtained by structurally modifying the Muth survival function. The proposed construction preserves the scale-family property while altering tail behavior and cumulative hazard growth. A statistical analysis was presented, including derivations of moments, the moment-generating function, and several entropy measures. Parameter estimation was carried out using maximum likelihood, and interval estimation was performed via the Fisher information matrix. The performance of the model was examined through extensive simulation studies and a real-world data application involving strength measurements of carbon fibers. In this application, the modified Muth distribution provides a competitive and, in several cases, improved fit compared with commonly used lifetime models.

CLC number: 60B12, 62G30

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AIMS Mathematics
Pages 6269-6296

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Cite this article:
Barakat HM, Bakouch HS, Elgawad MAA, et al. The modified Muth distribution: Statistical properties, entropy measures, and parameter estimation. AIMS Mathematics, 2026, 11(3): 6269-6296. https://doi.org/10.3934/math.2026259

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Received: 27 November 2025
Revised: 25 February 2026
Accepted: 03 March 2026
Published: 15 March 2026
©2026 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)