Finally, some real data has been taken to conduct an analysis and to discuss the effectiveness and advantages of the established work by comparing with other methods.
📌 3 Key Takeaways
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Objective & Hypothesis:The paper aims are to extend the theory to estimate the parameters of the exponentiated lifetime distribution.
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Key Findings & Data:For it, in this paper, we derived the probability density function, cumulative density, reliability function and the stress-strength parameter of the distribution.
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Conclusion & Impact:Finally, some real data has been taken to conduct an analysis and to discuss the effectiveness and advantages of the established work by comparing with other methods.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Exponentiated distributions family · Reliability function · Stress-strength parameter
Abstract
The paper aims are to extend the theory to estimate the parameters of the exponentiated lifetime distribution. For it, in this paper, we derived the probability density function, cumulative density, reliability function and the stress-strength parameter of the distribution. To estimate the parameters of such distribution, we considered the maximum likelihood and uniformly minimum variance unbiased methods. The validity of the proposed work has been conducted over the simulation study of both estimation methods under the special sub model as exponentiated inverse Gompertz distribution. Finally, some real data has been taken to conduct an analysis and to discuss the effectiveness and advantages of the established work by comparing with other methods.
POURREZA, H., JAMKHANEH, E. B., DEİRİ, E., GARG, H. (2022). Estimating the Parametric Functions and Reliability Measures for Exponentiated Lifetime Distributions Family. Gazi University Journal of Science, Cilt: 35 - Sayı: 4, 1665–1684. https://ajindex.com/articles/859462
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