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In this paper, we investigate a new model based on Burr X and Frhet distribution for extreme values and derive some of its properties. Maximum likelihood estimation along with asymptotic confidence intervals is considered for estimating the parameters of the distribution. We demonstrate empirically the flexibility of the distribution in modeling various types of real data. Furthermore, we also provide Bayes estimators and highest posterior density intervals of the parameters of the distribution using Markov Chain Monte Carlo (MCMC) methods.
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