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Bayesian Estimation of Transmuted Pareto Distribution for Complete and Censored Data

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Abstract

Transmuted distributions belong to the skewed family of distributions which are more flexible and versatile than the simple probability distributions. The focus of this article is the Bayesian estimation of three-parameter Transmuted Pareto distribution. In particular, we assumed noninformative and informative priors to obtain the posterior distributions. Bayesian point estimators and the associated precision measures are investigated under squared error loss function, precautionary loss function, and quadratic loss function. In addition to this, the Bayesian credible intervals are also computed under different priors. A simulation study using a Markov Chain Monte Carlo algorithm assuming uncensored and censored data in terms of different sample sizes and censoring rates is also a part of this study. The performance of Bayesian point estimators is assessed in term of posterior risks. Finally, two real life data sets of cardiovascular disease patients and of exceedances of Wheaton River flood are discussed in this article.

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Acknowledgements

The authors would like to thank the editor and three anonymous reviewers for their constructive comments to improve the manuscript.

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Authors and Affiliations

  1. Department of Mathematics and Statistics, Riphah International University, Islamabad, Pakistan

    Muhammad Aslam & Rahila Yousaf

  2. Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan

    Sajid Ali

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  1. Muhammad Aslam
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  2. Rahila Yousaf
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  3. Sajid Ali
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Correspondence to Sajid Ali.

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Appendix

Appendix

Real Data Sets used in Sect. 5 are given Tables 12 and 13.

Table 12 Real life data of the TPD recoding Survival Time (in days) of Patients
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Table 13 Exceedances of wheaton river flood data
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Aslam, M., Yousaf, R. & Ali, S. Bayesian Estimation of Transmuted Pareto Distribution for Complete and Censored Data. Ann. Data. Sci. 7, 663–695 (2020). https://doi.org/10.1007/s40745-020-00310-z

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  • DOI: https://doi.org/10.1007/s40745-020-00310-z

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