KUMARASWAMY TYPE II GENERALIZED TOPP-LEONE-G FAMILY OF DISTRIBUTIONS WITH APPLICATIONS
Abstract
In the field of reliability theory, practitioners have been working assiduously in recent years to propose new families of continuous probability distributions that extend the standard theoretical distribution that is currently in use. They have done this by hybridizing two or more probability models or by introducing one or more parameters to get more flexibility in fitting data from a variety of fields, including the environmental, economics, finance, and medical sciences. The T-X approach was used to establish the Kumaraswamy Type II Generalized Topp-Leone-G (KwT2GTL-G) family, which extends the Type II Generalized Topp-Leone-G family of distributions with extra shape parameters. A few statistical characteristics of the novel family were determined and examined. A sub-model emerged and MLE was used to estimate the model parameters. To demonstrate the value of the new family, two real-life data sets were used: a set that related to the relief times (in minutes) of patients taking an analgesic, and the other that related to the failure and service times for a windshield. The superior goodness-of-fits and empirical flexibility of the KwT2GTL-G distribution are demonstrated by comparisons with other distributions, including the Kumaraswamy Extension Exponential (KwEEx), Kumaraswamy Exponential (KEx), Exponential Generalized Exponentiated Exponential (EGEEx), and Exponentiated Weibull-Exponential (EWEx) distributions.. In the second dataset, the KwT2GTLEx distribution achieved an AIC value of 38.0489, outperforming the EGEEx distribution which had an AIC value of 39.6708 next to it. These findings highlight the KwT2GTL-G family's potential to enhance lifetime data modeling, which would have a substantial impact on engineering,...
References
Adepoju, K. A., &Chukwu, O. I. (2015). Maximum Likelihood Estimation of the Kumaraswamy Exponential Distribution with Applications, Journal of Modern Applied Statistical Methods, 14(1), 208-214. DOI: https://doi.org/10.22237/jmasm/1430453820
Ahmad, Z., Elgarhy, M., &Hamedani, G. G. (2018). A new Weibull-X family of distributions: properties, characterizations and applications. Journal of Statistical Distributions and Applications, 5, 1-18. DOI: https://doi.org/10.1186/s40488-018-0087-6
Alzaatreh A. Famoye C. & Lee C. (2014). The Gamma-Normal distribution: Properties and Applications. Computational Statistics & Data Analysis 69, 67-80, 2014. 163, 2014. DOI: https://doi.org/10.1016/j.csda.2013.07.035
Alzaatreh, A., Lee, C. &Famoye, F. (2013). A new method for generating families of continuous distributions. Metron, 71, 63-79. DOI: https://doi.org/10.1007/s40300-013-0007-y
Bello O.A., Doguwa S.I., Yahaya A. & Haruna M.J. (2021). A Type I Half Logistic Exponentiated - G family of distribution; properties and applications. Communication in Physical sciences 2020, 7(3): 147-163.
Bukoye, A., & Oyeyemi, G. M. (2018). On Development of Four-Parameters Exponentiated Generalized Exponential Distribution. Pak. J. Statist, 34(4), 331-358.
Cordeiro, G. M. & de Castro, M. (2011). A new family of generalized distribution.Journal of Statistical Computations and Simulation, 81, 883-898. DOI: https://doi.org/10.1080/00949650903530745
Cordeiro, G. M., Saboor, A., Khan, M. N.,Ozel, G., &Pascoa, M. A. (2016). The Kumaraswamy Exponential{Weibull Distribution: Theory and Applications. Hacettepe journal of mathematics and statistics, 45(4): 1203-1229. DOI: https://doi.org/10.15672/HJMS.20157612083
Elbatal, I., Louzada, F., &Granzotto, D. C. (2018). A new lifetime model: The Kumaraswamy Extension Exponential Distribution. Biostatistics and Bioinformatics, 2, 1-9. DOI: https://doi.org/10.31031/OABB.2018.02.000527
Elgarhy, M., Shakil, M., & Kibria, G. (2017). Exponentiated Weibull-Exponential Distribution with Applications. Applications and Applied Mathematics Journal (AAM), 12(2), 5.
Eugene, N., Lee, C. &Famoye, F. (2002). The beta-normal distribution and its applications. Communications in Statistics Theory and Methods, 31, 497- 512. DOI: https://doi.org/10.1081/STA-120003130
Greenwood, J. A., Landwehr, J.M., &Matalas, N.C.(1979). Probability weighted moments: Definitions and relations of parameters of several distributions expressible in inverse form. Water Resources Research, 15, 1049-1054. DOI: https://doi.org/10.1029/WR015i005p01049
Gross, A.J. and Clark, V.A. (1975) Survival Distributions Reliability Applications in the Biometrical Sciences. John Wiley, New York.
Hassan, A. S. & Elgarhy, M. (2016). Kumaraswamy Weibull- generated family of distributions with applications. Advances and Application in Statistics, 48, 205-239. DOI: https://doi.org/10.17654/AS048030205
Hassan, A. S., Elgarhy, M., & Ahmad, Z. (2019). Type II Generalized Topp-Leone Family of distributions: Properties and Applications. Journal of data science, 17(4). DOI: https://doi.org/10.6339/JDS.201910_17(4).0001
Ismail Kolawole Adekunle, Ibrahim Sule, & Olalekan Akanji Bello (2022). On The Properties of Topp-Leone Kumaraswamy Weibul Distribution with Applications To Biomedical Data. FUDMA Journal of Sciences, 6(5):169-179. DOI: https://doi.org/10.33003/fjs-2022-0605-1188
Ibrahim S, Doguwa S.I, Isah A & Haruna J.M.(2020). The Topp Leone Kumaraswamy-G Family of Distributions with Applications to Cancer Disease Data. Journal of Biostatistics and Epidemiology 6(1), 37-48.
Kolawole I.A., Abubakar Y., Sani I.D.& Aliyu Y. (2023). On the Exponentiated Type II Generalized Topp-Leone-G Family of Distribution: Properties and Applications. Communication in Physical sciences, 11(4):792-805.
Nofal, Z. M., Afify, A. Z., Yousof, H. M., & Cordeiro, G. M. (2017). The Generalized Transmuted-G Family of distributions. Communications in Statistics-Theory and Methods, 46(8), 4119-4136. DOI: https://doi.org/10.1080/03610926.2015.1078478
Tahir, M.H., Zubair, M., Mansoor M., Cordeiro G. M., Alizadeh, M. &Hamedani, G. G. (2016). A New Weibull-G Family of Distributions. Hacettepe Journal of Mathematics and Statistics, Vol. 45, 2, 629-647. DOI: https://doi.org/10.15672/HJMS.2015579686
Tahir, M. H., Cordeiro, G. M., Mansoor, M., & Zubair, M. (2015). The Weibull-Lomax distribution: Properties and applications. Hacettepe Journal of Mathematics andStatistics, 44, 461-480. DOI: https://doi.org/10.15672/HJMS.2014147465
Torabi, H., and Montazari, N.H. (2014). The logistic-uniform distribution and its application. Communications in Statistics Simulation and Computation 43:25512569. DOI: https://doi.org/10.1080/03610918.2012.737491
Yahaya A. & Doguwa S.I.S. (2021). On Theoretical Study of Rayleigh-Exponentiated Odd Generalized-X Family of Distributions.Transactions of the Nigerian Association of Mathematical Physics. (14),143 –154
Copyright (c) 2024 FUDMA JOURNAL OF SCIENCES
This work is licensed under a Creative Commons Attribution 4.0 International License.
FUDMA Journal of Sciences