On GAYUF Transformed Exponential Distribution and its Properties

In statistical literature, various methods exist for developing new distributions. This paper introduces a new distribution derived using the GAYUF transformation. We explore several structural properties of this distribution, including moments, moment generating function, mean, variance, hazard rate and its shape, survival function, and more. The parameters of the newly developed distribution are estimated using the maximum likelihood estimation (MLE) method and validated through simulation studies. Additionally, we apply the distribution to two real-world datasets to demonstrate its practical applications. The findings suggest that the new distribution is a robust tool for modelling and analysing data in engineering and other fields, providing enhanced fit and reliability for parameter estimation.

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Publication Details

Journal
African Journal of Mathematics and Statistics Studies
Published
2024-09-26
DOI
https://doi.org/10.52589/ajmss-4exhwpru
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
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article

On GAYUF Transformed Exponential Distribution and its Properties

A. S. Ajiboye, A. A. Akomolafe, Tanrıkulu Yusuf
African Journal of Mathematics and Statistics Studies
Statistical Distribution Estimation and Applications
article

On GAYUF Transformed Exponential Distribution and its Properties

A. S. Ajiboye, A. A. Akomolafe, Tanrıkulu Yusuf
article en

Abstract

In statistical literature, various methods exist for developing new distributions. This paper introduces a new distribution derived using the GAYUF transformation. We explore several structural properties of this distribution, including moments, moment generating function, mean, variance, hazard rate and its shape, survival function, and more. The parameters of the newly developed distribution are estimated using the maximum likelihood estimation (MLE) method and validated through simulation studies. Additionally, we apply the distribution to two real-world datasets to demonstrate its practical applications. The findings suggest that the new distribution is a robust tool for modelling and analysing data in engineering and other fields, providing enhanced fit and reliability for parameter estimation.

African Journal of Mathematics and Statistics StudiesVol. 7(3)
Openalex Percentile: Top 83%
Statistical Distribution Estimation and Applications
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On GAYUF Transformed Exponential Distribution and its Properties — A. S. Ajiboye, A. A. Akomolafe, et al. · African Journal of Mathematics and Statistics Studies (2024) | TGRS Research Map | TGRS