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General Results for the Transmuted Family of Distributions and New Models

Author

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  • Marcelo Bourguignon
  • Indranil Ghosh
  • Gauss M. Cordeiro

Abstract

The transmuted family of distributions has been receiving increased attention over the last few years. For a baseline G distribution, we derive a simple representation for the transmuted- G family density function as a linear mixture of the G and exponentiated- G densities. We investigate the asymptotes and shapes and obtain explicit expressions for the ordinary and incomplete moments, quantile and generating functions, mean deviations, Rényi and Shannon entropies, and order statistics and their moments. We estimate the model parameters of the family by the method of maximum likelihood. We prove empirically the flexibility of the proposed model by means of an application to a real data set.

Suggested Citation

  • Marcelo Bourguignon & Indranil Ghosh & Gauss M. Cordeiro, 2016. "General Results for the Transmuted Family of Distributions and New Models," Journal of Probability and Statistics, Hindawi, vol. 2016, pages 1-12, January.
    • Handle: RePEc:hin:jnljps:7208425
    DOI: 10.1155/2016/7208425
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    Cited by:

    1. Shahzad Hussain & Sajjad Haider Bhatti & Tanvir Ahmad & Muhammad Ahmed Shehzad, 2021. "Parameter estimation of the Pareto distribution using least squares approaches blended with different rank methods and its applications in modeling natural catastrophes," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(2), pages 1693-1708, June.
    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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