Abstract
Classical distributions do not always provide reasonable fit to all forms of datasets, hence the need to generalize existing distributions to enhance their flexibility in modeling of data. The study developed the odd Chen-G family of distributions. It derives the statistical properties of the new family such as the quantile, moments, and order statistics. Though capable of generalizing other distributions, the study proposed three special distributions; odd Chen Burr III, odd Chen Lomax and odd Chen Weibull distributions. The application of the new family is then demonstrated using real data.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Zubair A (2018) The Zubair-G family of distributions: properties and applications. Annals of Data Science. https://doi.org/10.1007/s40745-018-0169-9
Nasiru S (2018) Extended odd Fréchet-G family of distributions. J Probab Stat. https://doi.org/10.1155/2018/2931326
Cordeiro GM, de Castro M (2011) A new family of generalized distributions. J Stat Comput Simul 81(7):883–898
Eugene N, Lee C, Famoye F (2002) Beta-normal distribution and its applications. Commun Stat Theory Methods 31(4):497–512
Alzaatreh A, Lee C, Famoye F (2013) A new method for generating families of continuous distributions. Metron 71(1):63–79
Alzaghal A, Famoye F, Lee C (2013) Exponentiated T-X family of distributions with some applications. Int J Stat Probab 2(3):31–49
Nasiru S, Mwita PN, Ngesa O (2017) Exponentiated generalized Transformed-Transformer family of distributions. J Stat Econ Methods 6(4):17
Bourguignon M, Silva RB, Cordeiro GM (2014) The weibull-G family of probability distributions. J Data Sci 12:53–68
Tahir MH, Cordeiro GM, Alizadeh M, Mansoor M, Zubair M, Hamedani GG (2015) The odd generalized exponential family of distributions with applications. J Stat Distrib Appl 2(1):1–28
Brito E, Cordeiro GM, Yousof HM, Alizadeh M, Silva GO (2017) The Topp–Leone odd log-logistic family of distributions. J Stat Comput Simul 87(15):3040–3058
Haq MA, Elgarhy M (2018) The odd Fréchet-G family of probability distributions. J Stat Appl Probab 7(1):189–203
Chen Z (2000) A new two-parameter lifetime distribution with bathtub shape or increasing failure rate function. Stat Probab Lett 49:155–161
Xie M, Tang Y, Goh TN (2002) A modified Weibull extension with bathtub-shaped failure rate function. Reliab Eng Syst Saf 76(3):279–285
Rényi A (1961) On measures of entropy and information. In: Proceedings of the fourth berkeley symposium on mathematical statistics and probability, contributions to the theory of statistics, vol 1, pp 547–561
Pak A, Mahmoudi MR (2018) Estimating the parameters of Lomax distribution from imprecise information. J Stat Theory Appl 17(1):122–135
Bolker B (2014). Tools for general maximum likelihood estimation. R development core team
Doostmoradi A, Zadkarami MR, Sheykhabad AR (2014) A new modified Weibull distribution and its applications. J Stat Res 11:97–118
Aarset MV (1987) How to Identify Bathtub Hazard Rate. IEEE Trans Reliab 36:106–108
Sylwia KB (2007) Makeham’s generalised distribution, computational methods. Sci Technol 13:113–120
Acknowledgement
The authors would like to thank the anonymous reviewers and editors whose helpful comments and suggestions improved the quality of the paper.
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Conflict of interest
The authors declare that there are no conflict of interest regarding the publication of this article.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Anzagra, L., Sarpong, S. & Nasiru, S. Odd Chen-G Family of Distributions. Ann. Data. Sci. 9, 369–391 (2022). https://doi.org/10.1007/s40745-020-00248-2
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40745-020-00248-2