Applications to Physical Data Using Four-Parameter Inverted Topp-Leone Model

Authors

  • Amal Soliman Hassan Department of mathematical Statistics, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza, Egypt
  • Ehab Mohamed Almetwally Department of Mathematics and Statistics, Faculty of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia

Keywords:

Inverted Topp-Leone distribution, maximum likelihood, Bayesian method, stress strength model, entropy measures

Abstract

The Kumaraswamy Marshall-Olkin inverted Topp-Leone (KMOITL) distribution is a new four-parameter generalized version of the inverted Topp-Leone (ITL) distribution proposed in this research. The Marshall-Olkin ITL distribution is a novel model, while the Kumaraswamy ITL and ITL distributions are existing sub-models in the proposed distribution. Different shapes of the density and hazard rate functions are provided by the KMOITL distribution, which has three shape parameters and one scale parameter. The KMOITL’s density function can be written as a linear combination of the inverted Topp-Leone density. We construct several statistical expressions for the proposed KMOITL model. The KMOITL distribution parameters are estimated using maximum likelihood and Bayesian estimation techniques. In light of symmetric and asymmetric loss functions, Bayesian estimators are explored. The performance of the suggested estimating techniques is evaluated using simulation results. Finally, the suggested model is tested based on physical real data, with the findings demonstrating the KMOITL distribution’s higher performance over some other models.

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Published

2024-03-31

How to Cite

Soliman Hassan, A. ., & Mohamed Almetwally, E. . (2024). Applications to Physical Data Using Four-Parameter Inverted Topp-Leone Model. Thailand Statistician, 22(2), 430–457. Retrieved from https://ph02.tci-thaijo.org/index.php/thaistat/article/view/253433

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