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Odd Chen-G Family of Distributions

Author

Listed:
  • Lea Anzagra

    (University for Development Studies)

  • Solomon Sarpong

    (University for Development Studies)

  • Suleman Nasiru

    (University for Development Studies)

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.

Suggested Citation

  • Lea Anzagra & Solomon Sarpong & Suleman Nasiru, 2022. "Odd Chen-G Family of Distributions," Annals of Data Science, Springer, vol. 9(2), pages 369-391, April.
    • Handle: RePEc:spr:aodasc:v:9:y:2022:i:2:d:10.1007_s40745-020-00248-2
    DOI: 10.1007/s40745-020-00248-2
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    References listed on IDEAS

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    1. Suleman Nasiru & Peter N. Mwita & Oscar Ngesa, 2017. "Exponentiated Generalized Transformed-Transformer Family of Distributions," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 6(4), pages 1-1.
    2. Suleman Nasiru, 2018. "Extended Odd Fréchet-G Family of Distributions," Journal of Probability and Statistics, Hindawi, vol. 2018, pages 1-12, December.
    3. Chen, Zhenmin, 2000. "A new two-parameter lifetime distribution with bathtub shape or increasing failure rate function," Statistics & Probability Letters, Elsevier, vol. 49(2), pages 155-161, August.
    4. Ayman Alzaatreh & Carl Lee & Felix Famoye, 2013. "A new method for generating families of continuous distributions," METRON, Springer;Sapienza Università di Roma, vol. 71(1), pages 63-79, June.
    Full references (including those not matched with items on IDEAS)

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