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The Inverted Exponentiated Gamma Distribution: A Heavy-Tailed Model with Upside Down Bathtub Shaped Hazard Rate

Author

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  • Abhimanyu Singh Yadav

    (Department of Statistics, Central University of Rajasthan)

Abstract

In this article, we proposed and studied the inverted exponentiated gamma distribution (IEGD). IEGD is obtained by considering the inverse transformation of exponentiated gamma variate. This distribution has been motivated by the extensive use of the exponentiated gamma model in many applied areas and also due to the fact that this new generalization provides more flexibility to analyze real data with upside down bathtub (UBT) hazard rate. The shape of the distribution has been traced mathematically and found that the proposed model is compatible with UBT hazard rate models. The tail area property is also presented based on the idea of Marshall and Olkin (2007) and it is concluded that the new model belongs to the family of heavy-tailed distributions. Some other characteristics such as reliability, hazard, the quantile function, skewness and kurtosis, stochastic ordering, stress-strength reliability and order statistics have been explicitly derived. The classical and Bayesian estimation procedures have been discussed to estimate the unknown parameter of IEGD. The performances of classical and Bayes estimators are studied in terms of average mean square error (MSE) by conducting Monte Carlo simulations. Finally, a real data set with UBT type hazard rate is analyzed for the illustrative purpose of the study.

Suggested Citation

  • Abhimanyu Singh Yadav, 2019. "The Inverted Exponentiated Gamma Distribution: A Heavy-Tailed Model with Upside Down Bathtub Shaped Hazard Rate," Statistica, Department of Statistics, University of Bologna, vol. 79(3), pages 339-360.
    • Handle: RePEc:bot:rivsta:v:79:y:2019:i:3:p:339-360
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