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In this article, based on progressively Type-II censored schemes under step-stress partially accelerated life test model, the maximum likelihood, Bayes, and two parametric bootstrap methods are used for estimating the unknown parameters of the Kumaraswamy inverse Weibull distribution and the acceleration factor. Asymptotic confidence interval estimates of the model parameters and the acceleration factor are also evaluated by using Fisher information matrix. The classical Bayes estimators cannot be obtained in explicit form, so Markov chain Monte Carlo method is used to tackle this problem, which allows us to construct the credible interval of the involved parameters. Finally, analysis of a simulated data set has been also presented for illustrative purposes

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