A Novel Distribution on the Unit Interval with Properties and Applications for Electronic Components

This paper introduces a novel continuous probability distribution on the unit interval called the unit Jamal distribution and explores its properties. The proposed distribution performs well in modeling bathtub-shaped data, effectively capturing its characteristic hazard rate behavior. Key mathematical characteristics such as moments, the moment generating function, order statistics, entropy, and the quantile function are thoroughly derived. Parameter estimation is conducted using maximum likelihood and Bayesian estimation methods. A simulation study is conducted to evaluate the accuracy of parameter estimates and to examine the distribution’s behavior. Additionally, the applicability of the proposed distribution is demonstrated through analysis of two real-world datasets, allowing for a comparison of its performance against existing models.

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Publication Details

Journal
Axioms
Published
2026-05-12
DOI
https://doi.org/10.3390/axioms15050359
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

A Novel Distribution on the Unit Interval with Properties and Applications for Electronic Components

Mohamed A. Abd Elgawad, Muhammad Imran, Shahid Mohammad, Farrukh Jamal
Axioms
Statistical Distribution Estimation and Applications
article

A Novel Distribution on the Unit Interval with Properties and Applications for Electronic Components

Mohamed A. Abd Elgawad, Muhammad Imran, Shahid Mohammad, Farrukh Jamal
article en

Abstract

This paper introduces a novel continuous probability distribution on the unit interval called the unit Jamal distribution and explores its properties. The proposed distribution performs well in modeling bathtub-shaped data, effectively capturing its characteristic hazard rate behavior. Key mathematical characteristics such as moments, the moment generating function, order statistics, entropy, and the quantile function are thoroughly derived. Parameter estimation is conducted using maximum likelihood and Bayesian estimation methods. A simulation study is conducted to evaluate the accuracy of parameter estimates and to examine the distribution’s behavior. Additionally, the applicability of the proposed distribution is demonstrated through analysis of two real-world datasets, allowing for a comparison of its performance against existing models.

AxiomsVol. 15(5)
Imam Mohammad ibn Saud Islamic University (SA), Pakistan Agricultural Research Council (PK), University of Wisconsin–Oshkosh (US), University of Tabuk (SA)
Al-Imam Muhammad Ibn Saud Islamic University
Openalex Percentile: Top 4%
Statistical Distribution Estimation and Applications
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A Novel Distribution on the Unit Interval with Properties and Applications for Electronic Components — Mohamed A. Abd Elgawad, Muhammad Imran, et al. · Axioms (2026) | TGRS Research Map | TGRS