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The Markov chain Monte Carlo (MCMC) technique is applied for estimating the Complementary Exponential Power (CEP) distribution's parameters through the analysis of complete sample in this article. With the help of the Bayesian and the Maximum Likelihood techniques, the unknown parameters of the model are estimated. To find Complementary Exponential Power distribution's parameters' Bayesian estimates, a new methodology is developed, via simulation method of MCMC through the application ofdoi:10.35940/ijeat.b2093.1210220 fatcat:3f3linq4r5cyznsulwcymruee4