Main Article Content
In this work, a new distribution called the Chen Pareto distribution was derived using the Chen-G family of distributions. The mixture representation of the distribution was obtained. Furthermore, some statistical properties such as moments, moment generating functions, order statistics properties of the distribution were explored. The parameter estimation for the distribution was done using the maximum likelihood estimation method and the performance of estimators was assessed by conducting an extensive simulation study. The distribution was applied to a real dataset in which it performs best when compared to some related distributions
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
- Anzagra,L. , Sarpong,S., Suleman Nasiru (2020).Chen-G class of distributions, Cogent Mathematics and Statistics, 7:1, 1721401
- Lee, S., Kim, J. H. (2018) Exponentiated generalized Pareto distribution: Properties and applications towards extreme value theory. Communications in Statistics-Theory and Methods.1–25.
- Brazauskas, V., Serﬂing, R.(2003). Favorable estimators for ﬁtting Pareto models: A study using goodness-of-ﬁt measures with actual data. ASTIN Bulletin: The Journal of the IAA. 33(2):365–81.
- Farshchian, M., Posner, F. L.(2010)The Pareto distribution for low grazing angle and high resolution X-band sea clutter. Naval Research Lab Washington DC. 5.
- Korkmaz, M., Altun, E., Yousof, H., Aﬁfy, A., Nadarajah, S. (2018). The Burr X Pareto Distribution: Properties, Applications and VaR Estimation. Journal of Risk and Financial Management.11(1):1
- Alzaatreh, A., Famoye, F., Lee, C. (2013) Weibull-Pareto distribution and its applications. Communica- tions in Statistics Theory and Methods.42(9):1673–1691.
- Akinsete A, Famoye F, Lee C. (2008) The beta-Pareto distribution. Statistics. 42(6):547–63.
- Pereira, M.B., Silva, R.B., Zea, L.M., Cordeiro, G.M. (2012) The kumaraswamy Pareto distribution. arXiv preprint arXiv:1204.1389.
- Gupta, R.C., Gupta, P.L., Gupta, R.D. (1998) Modeling failure time data by Lehman alternatives. Com- munications in Statistics-Theory and methods.27(4):887–904.
- Nadarajah, S. (2005) Exponentiated Pareto distributions. Statistics.39(3):255–60.
- Mahmoudi, E.(2011) The beta generalized Pareto distribution with application to lifetime data. Math- ematics and computers in Simulation.81(11):2414–2430.
- Alzaatreh, A., Famoye, F., Lee, C.(2012) Gamma Pareto Distribution and Applications, Journal of Modern Applied Statistical Methods. 11(1):7
- Faton, M., Llukan, P.(2014) Transmuted Pareto Distribution. ProbStat Forum. 7:1-11
- Shannon, C.E. (1948) A mathematical theory of communication. Bell Syst Tech J 27:379–423
- Akinsete, A., Famoye, Felix., Lee, Carl.(2008) The beta-Pareto distribution,Statistics,42:6,547- 563
- Rahman, M., Al-Zahrani, B., Shahbaz, M.Q. (2018) Cubic Transmuted Pareto Distribution, Annals of Data Science,https://doi.org/10.1007/s40745-018-0178-8
- Mudholkar, G.S., Huston, A.D.(1996) The exponentiated Weibull family: some properties and a ﬂood data application. Commun Stat Theory Methods 23:1149–1171