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Article

Statistical Inference of the Beta Binomial Exponential 2 Distribution with Application to Environmental Data

by
Osama H. Mahmoud Hassan
1,*,
Ibrahim Elbatal
2,
Abdullah H. Al-Nefaie
1 and
Ahmed R. El-Saeed
3
1
Department of Quantitative Methods, School of Business, King Faisal University, Al Hofuf 31982, Al-Ahsa, Saudi Arabia
2
Department of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 11432, Saudi Arabia
3
Department of Basic Sciences, Obour High Institute for Management & Informatics, Obour 11848, Egypt
*
Author to whom correspondence should be addressed.
Axioms 2022, 11(12), 740; https://doi.org/10.3390/axioms11120740
Submission received: 10 November 2022 / Revised: 11 December 2022 / Accepted: 14 December 2022 / Published: 17 December 2022
(This article belongs to the Special Issue Computational Statistics & Data Analysis)

Abstract

A new four-parameter lifetime distribution called the beta binomial exponential 2 (BBE2) distribution is proposed. Some mathematical features, including quantile function, moments, generating function and characteristic function, of the BBE2 distribution, are computed. When the life test is truncated at a predetermined time, acceptance sampling plans (ASP) are constructed for the BBE2 distribution. The truncation time is supposed to represent the median lifetime of the BBE2 distribution with predetermined factors for the smallest sample size required to guarantee that the prescribed life test is achieved at a given consumer’s risk. Some numerical results for a given consumer’s risk, BBE2 distribution parameters and truncation time are derived. Classical (maximum likelihood and maximum product of spacing estimation methods) and Bayesian estimation approaches are utilized to estimate the model parameters. The performance of the model parameters is examined through the simulation study by using the three different approaches of estimation. Subsequently, we examine real-world data applications to demonstrate the versatility and potential of the BBE2 model. A real-world application demonstrates that the new distribution can offer a better fit than other competitive lifetime models.
Keywords: beta family; acceptance sampling plan; binomial exponential 2; moments; Bayesian approach; maximum product spacing; maximum likelihood beta family; acceptance sampling plan; binomial exponential 2; moments; Bayesian approach; maximum product spacing; maximum likelihood

Share and Cite

MDPI and ACS Style

Hassan, O.H.M.; Elbatal, I.; Al-Nefaie, A.H.; El-Saeed, A.R. Statistical Inference of the Beta Binomial Exponential 2 Distribution with Application to Environmental Data. Axioms 2022, 11, 740. https://doi.org/10.3390/axioms11120740

AMA Style

Hassan OHM, Elbatal I, Al-Nefaie AH, El-Saeed AR. Statistical Inference of the Beta Binomial Exponential 2 Distribution with Application to Environmental Data. Axioms. 2022; 11(12):740. https://doi.org/10.3390/axioms11120740

Chicago/Turabian Style

Hassan, Osama H. Mahmoud, Ibrahim Elbatal, Abdullah H. Al-Nefaie, and Ahmed R. El-Saeed. 2022. "Statistical Inference of the Beta Binomial Exponential 2 Distribution with Application to Environmental Data" Axioms 11, no. 12: 740. https://doi.org/10.3390/axioms11120740

APA Style

Hassan, O. H. M., Elbatal, I., Al-Nefaie, A. H., & El-Saeed, A. R. (2022). Statistical Inference of the Beta Binomial Exponential 2 Distribution with Application to Environmental Data. Axioms, 11(12), 740. https://doi.org/10.3390/axioms11120740

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