[0,1] Truncated Exponential Marshall-Olkin-Gompertz Distribution: Properties and Applications
Main Article Content
Abstract
In this paper, a new compound distribution termed as [0,1]Truncated Exponential Marshall-Olkin-Gompertz (TEMO-Go)is introduced. Several essential statistical properties of TEMO-Go distribution were studied. The estimation of distribution parameters was performed using the maximum likelihood estimation method, the flexibility of the new distribution was examined using two real data. The suitability of the proposed distribution indicates that it performs positively when compared to the existing distributions.
Downloads
Article Details
References
Abid, S. H., Al-Noor, N. H., & Boshi, M. A., (2018), [0,1] Truncated Generalized Gamma – Generalized Gamma Distribution, Journal of Iraqi Al-Khwarizmi Society, 2, 135-148.
Ahmad, Z., & Hussain, Z. (2017), New Extended Weibull Distribution, Circulation in Computer Science, 2(4), 68-75.
Alizadeh, M., Cordeiro, G. M., Pinho, L. G. B., & Ghosh, I. (2017), The Gompertz-G family of distributions, Journal of Statistical Theory and Practice, 11(1), 179-207.
Al-Noor, N. H., & Hadi, H. H., (2020), Properties and Applications of Truncated Exponential Marshall Olkin Weibull Distribution, Accepted in Ibn Al-Haitham 2nd International Conference for Pure and Applied Science (IHICPAS).
Atanda, O. D., Mabur, T. M., & Onwuka, G. I. (2020), A New Odd Lindley-Gompertz Distribution: Its Properties and Applications, Asian Journal of Probability and Statistics, 29-47.
da Silva, R. C., Sanchez, J. J., Lima, F. P., & Cordeiro, G. M. (2015), The kumaraswamy gompertz distribution, Journal of Data Science, 13(2), 241-259.
Eghwerido, J., Zelibe, S., & Efe-Eyefia, E. (2020), Gompertz-Alpha Power Iverted Exponential Distribution: Properties and Applications, Thailand Statistician, 18(3), 319-332.
Hyndman, R. J., & Fan, Y. (1996), Sample quantiles in statistical packages, The American Statistician, 50(4), 361-365.
Jafari, A. A., Tahmasebi, S., & Alizadeh, M. (2014), The beta-Gompertz distribution, Revista Colombiana de Estadistica, 37(1), 141-158.
Khaleel, M. A., Al-Noor, N. H., & Abdal-Hameed, M. K.(2020), Marshall Olkin exponential Gompertz distribution: Properties and applications, Periodicals of Engineering and Natural Sciences,8(1), 298-312.
Khaleel, M. A., Ibrahim, N. A., Shitan, M., & Merovci, F. (2018), New extension of Burr type X distribution properties with application, Journal of King Saud University-Science, 30(4), 450-457.
Khaleel, M. A., Oguntunde, P. E., Ahmed, M. T., Ibrahim, N. A., & Loh, Y. F. (2020), The Gompertz Flexible Weibull Distribution and its Applications, Malaysian Journal of Mathematical Sciences, 14(1), 169-190.
Lenart, A. (2012), The Gompertz distribution and maximum likelihood estimation of its parameters: a revision, MPDIR Work Pap, 49, 0-19.
Marshall, A. W., & Olkin, I. (1997), A new method for adding a parameter to a family of distributions with application to the exponential and Weibull families, Biometrika, 84(3), 641-652.
Merovci, F., Khaleel, M. A., Ibrahim, N. A., & Shitan, M. (2016), The beta Burr type X distribution properties with application, SpringerPlus, 5(1), 697.
Nwezza, E. E., & Ugwuowo, F. I. (2020), The Marshall-Olkin Gumbel-Lomax distribution: properties and applications, Heliyon, 6(3), e03569.
Oguntunde, P. E., Khaleel, M. A., Ahmed, M. T., & Okagbue, H. I. (2019), The Gompertz fréchet distribution: properties and applications, Cogent Mathematics & Statistics, 6(1), 1568662.
Oguntunde, P. E., Khaleel, M. A., Ahmed, M. T., Adejumo, A. O., & Odetunmibi, O. A. (2017), A new generalization of the lomax distribution with increasing, decreasing, and constant failure rate, Modelling and Simulation in Engineering, Volume 2017, Article ID 6043169, 6 pages.
Ohishi, K., Okamura, H., & Dohi, T. (2009), Gompertz software reliability model: Estimation algorithm and empirical validation, Journal of Systems and software, 82(3), 535-543.
Pollard, J. H., & Valkovics, E. J. (1992), The Gompertz distribution and its applications, Genus, vol. 48, no. 3, pp. 15-28.