Development of the new beta Prime-G family of distributions for advanced modeling of radiation data

Suleiman, Ahmad Abubakar and Althobaiti, Zahrah Fayez and Daud, Hanita and Waeleh, Nazreen and Abd Elwahab, Maysaa Elmahi and Idress, Raga (2026) Development of the new beta Prime-G family of distributions for advanced modeling of radiation data. Journal of Radiation Research and Applied Sciences, 19. pp. 1-19. ISSN 1687-8507

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Abstract

Radiation data often exhibit complex structures and patterns, posing significant challenges for statistical modeling and analysis. Traditional models may fail to capture the underlying relationships and behaviors of radiation data, leading to inaccurate predictions and risk assessments. This paper introduces the New Beta Prime-Generalized (NBP-G) family of distributions and applies it to develop a new model called the NBP-Weibull distribution. The NBP-Weibull distribution offers enhanced distributional flexibility, capable of representing a wide range of density shapes, including sharply right-skewed and near-symmetric forms. Additionally, the NBP-Weibull model accommodates various types of increasing hazard rate patterns, including those that increase rapidly after an initial flat period, making it crucial for robust reliability and risk assessment applications in radiation engineering. Some desirable statistical properties of the NBP-G family, including moments, the moment-generating function, Renyi and Tsallis entropies, the stress-strength function, and order statistics, are derived. The parameters of the NBP-G family are estimated using the maximum likelihood estimation method. A Monte Carlo simulation study is conducted to evaluate the performance of the MLE method. The NBP-Weibull model is applied to three radiation datasets, and its performance is evaluated using goodness-of-fit criteria. The results show the NBP-G family provides improved fit under selected criteria for modeling complex data patterns. This research highlights the NBP-Weibull model's effectiveness in modeling radiation data and its potential for accurate predictions and insights in this field.

Item Type:	Article
Uncontrolled Keywords:	Statistical model, Generalized family of distributions, T-X method, R´enyi entropy, Maximum likelihood estimation, Radiation science
Divisions:	Faculty Of Electronics And Computer Technology And Engineering
Depositing User:	Sabariah Ismail
Date Deposited:	20 Jul 2026 08:12
Last Modified:	20 Jul 2026 08:12
URI:	http://eprints.utem.edu.my/id/eprint/30150
Statistic Details:	View Download Statistic

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