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Cubic Transmuted-G Family of Distributions and Its Properties

Author

Listed:
  • Aslam Muhammad

    (Department of Statistics, Quaid-i-Azam University, Islamabad44000, Pakistan)

  • Hussain Zawar
  • Asghar Zahid

    (Department of Statistics, Quaid-i-Azam University, Islamabad44000, Pakistan)

Abstract

In this article, a new family of distributions is introduced by using transmutation maps. The proposed family of distributions is expected to be useful in modeling real data sets. The genesis of the proposed family, including several statistical and reliability properties, is presented. Methods of estimation like maximum likelihood, least squares, weighted least squares, and maximum product spacing are discussed. Maximum likelihood estimation under censoring schemes is also considered. Further, we explore some special models of the proposed family of distributions and examined different properties of these special models. We compare three particular models of the proposed family with several existing distributions using different information criteria. It is observed that the proposed particular models perform better than different competing models. Applications of the particular models of the proposed family of distributions are finally presented to establish the applicability in real life situations.

Suggested Citation

  • Aslam Muhammad & Hussain Zawar & Asghar Zahid, 2018. "Cubic Transmuted-G Family of Distributions and Its Properties," Stochastics and Quality Control, De Gruyter, vol. 33(2), pages 103-112, December.
    • Handle: RePEc:bpj:ecqcon:v:33:y:2018:i:2:p:103-112:n:1
    DOI: 10.1515/eqc-2017-0027
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    Citations

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    Cited by:

    1. Joseph Thomas Eghwerido & Pelumi E. Oguntunde & Friday Ikechukwu Agu, 2023. "The Alpha Power Marshall-Olkin-G Distribution: Properties, and Applications," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 172-197, February.
    2. Abdisalam Hassan Muse & Samuel M. Mwalili & Oscar Ngesa, 2021. "On the Log-Logistic Distribution and Its Generalizations: A Survey," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 10(3), pages 1-93, June.

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