Inference for Burr-XII with progressive Type-II censoing with random removals in step-stress partially accelerated life test

Based on progressive Type-II censoring with random removals, this paper develops the estimation of parameters from Burr-XII distribution in step-stress partially ALT under tampered random variable model. MLEs for unknown parameters have been obtained and a hybrid algorithm combined Gibbs sampling and Metropolis-Hastings sampling has been used to derive Bayesian estimation. Asymptotic normality theory and MCMC method are employed to construct the confidence intervals and HPD credible intervals at three different confidence levels. Monte Carlo simulations are then carried out for comparing the statistical performances in terms of RABias and MSE. Finally, one data set is analyzed for illustrative purposes with interval estimation and trace plot of parameter sampled by using the hybrid algorithm mentioned above.