Home / Current Issue / Paper 1723511
A Flexible Odd Exponentiated Half-Logistic Exponentiated Exponential Model for Lifetime and Reliability Data: Applications to Real-Life Datasets
Subject area: Science,Engineering and Technology · Area of research: Mathematical Statistics
Abstract
Flexible probability distributions are important for modelling real-life data exhibiting skewness, kurtosis and diverse distributional characteristics. This study investigates the applicability of the Odd Exponentiated Half-Logistic Exponentiated Exponential (OEHL-EE) distribution, a four-parameter extension of the Exponentiated Exponential distribution constructed using the Odd Exponentiated Half-Logistic-G generator. Although the theoretical properties of the OEHL-EE distribution have been established, its practical performance is examined in this study through applications to four real-life datasets. The datasets comprise monthly inflation rates in Nigeria from January 2003 to June 2023, fatigue-fracture lifetimes of Kevlar 373/epoxy specimens, the Gross and Clark dataset, and turbocharger failure times. The proposed model is compared with several competing distributions using maximum likelihood estimation and a collection of model-selection and goodness-of-fit criteria, including the negative log-likelihood, Akaike Information Criterion, Consistent Akaike Information Criterion, Hannan–Quinn Information Criterion, Bayesian Information Criterion, Anderson–Darling, Cramér–von Mises and Kolmogorov–Smirnov statistics. The results reported in the study show that the OEHL-EE model provides a close fit to the four datasets and generally records favourable goodness-of-fit measures relative to the competing models considered. Graphical comparisons based on fitted density and cumulative distribution functions further demonstrate the ability of the proposed model to describe the empirical behaviour of the datasets. The findings illustrate the practical usefulness of the OEHL-EE distribution for modelling skewed lifetime, reliability and other positive-valued data.
Keywords
Odd Exponentiated Half-Logistic; Exponentiated Exponential; lifetime data; reliability; maximum likelihood estimation; goodness of fit; model selection.
References
[1] Z. Afify, C. Lee, and A. Alzaatreh, “Odd exponentiated half logistic distribution: Properties and applications,” Journal of Statistical Theory and Practice, vol. 11, no. 3, pp. 417–432, 2017.
[2] G. M. Cordeiro and M. de Castro, “A new family of generalized distributions,” Journal of Statistical Computation and Simulation, vol. 81, no. 7, pp. 883–898, 2011. Taylor & Francis
[3] R. D. Gupta and D. Kundu, “Exponentiated exponential family: An alternative to gamma and Weibull distributions,” Biometrical Journal, vol. 43, no. 1, pp. 117–130, 2001. Wiley
[4] A. I. Ishaq, A. A. Abiodun, A. A. Suleiman, A. Usman, A. S. Mohammed, and M. Tasiu, “Modelling Nigerian inflation rates from January 2003 to June 2023 using newly developed inverse power chi-square distribution,” in Proceedings of the 4th International Conference on Data Analytics for Business and Industry, 2023. IEEE
[5] K. Jayakumar and M. G. Babu, “T-transmuted X family of distributions,” Statistica, vol. 77, no. 3, pp. 261–276, 2017.
[6] A. S. Mohammed and F. I. Ugwuowo, “A new four-parameter Weibull distribution with application to failure time data,” FUDMA Journal of Sciences, vol. 4, no. 3, pp. 563–575, 2020. FUDMA Journal of Sciences
[7] O. D. Ogunwale, T. M. Ayeni, F. A. Osunronbi, R. A. Adeleke, and E. A. Odukoya, “The new Exponential–Exponential distribution: Theory and properties,” Quest Journal of Research in Applied Mathematics, vol. 8, no. 8, pp. 13–19, 2022.
[8] O. I. Oseghale, V. E. Laoye, and Z. A. Adeleke, “Half logistic exponentiated inverted Weibull distribution: Properties and application to survival data,” International Journal of Applied Science and Mathematical Theory, vol. 11, no. 2, pp. 100–110, 2025. IIARD Journals
[9] E. A. Owoloko, P. E. Oguntunde, and A. O. Adejumo, “Performance rating of the transmuted exponential distribution: An analytical approach,” SpringerPlus, vol. 4, Art. no. 818, 2015. Springer
[10] Oluyede, T. Moakofi, and G. Lekono, “The new Marshall–Olkin–type II exponentiated half-logistic–odd Burr X-G family of distributions with properties and applications,” Stats, vol. 8, no. 2, Art. no. 26, 2025. MDPI
[11] E. W. Stacy, “A generalization of the gamma distribution,” Annals of Mathematical Statistics, vol. 33, no. 3, pp. 1187–1192, 1962. Project Euclid
[12] W. Weibull, “A statistical distribution function of wide applicability,” Journal of Applied Mechanics, vol. 18, no. 3, pp. 293–297, 1951. ASME
How to cite this paper
@article{1723511,
author = {Adewoye, Kunle Bayo, Azeez, Olasunkanmi, Isiaka, Azeez, Olabisi Omodasola},
title = {A Flexible Odd Exponentiated Half-Logistic Exponentiated Exponential Model for Lifetime and Reliability Data: Applications to Real-Life Datasets},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {3},
pages = {3728-3739},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1723511.pdf},
abstract = {Flexible probability distributions are important for modelling real-life data exhibiting skewness, kurtosis and diverse distributional characteristics. This study investigates the applicability of the Odd Exponentiated Half-Logistic Exponentiated Exponential (OEHL-EE) distribution, a four-parameter extension of the Exponentiated Exponential distribution constructed using the Odd Exponentiated Half-Logistic-G generator. Although the theoretical properties of the OEHL-EE distribution have been established, its practical performance is examined in this study through applications to four real-life datasets. The datasets comprise monthly inflation rates in Nigeria from January 2003 to June 2023, fatigue-fracture lifetimes of Kevlar 373/epoxy specimens, the Gross and Clark dataset, and turbocharger failure times. The proposed model is compared with several competing distributions using maximum likelihood estimation and a collection of model-selection and goodness-of-fit criteria, including the negative log-likelihood, Akaike Information Criterion, Consistent Akaike Information Criterion, Hannan–Quinn Information Criterion, Bayesian Information Criterion, Anderson–Darling, Cramér–von Mises and Kolmogorov–Smirnov statistics. The results reported in the study show that the OEHL-EE model provides a close fit to the four datasets and generally records favourable goodness-of-fit measures relative to the competing models considered. Graphical comparisons based on fitted density and cumulative distribution functions further demonstrate the ability of the proposed model to describe the empirical behaviour of the datasets. The findings illustrate the practical usefulness of the OEHL-EE distribution for modelling skewed lifetime, reliability and other positive-valued data.},
keywords = {Odd Exponentiated Half-Logistic; Exponentiated Exponential; lifetime data; reliability; maximum likelihood estimation; goodness of fit; model selection.},
month = {September},
}