Statistical Inference of Weighted Exponential Distribution under Joint Progressive Type-II Censoring

The weighted exponential distribution is a promising skewed in the life-testing experiment. joint progressive type-II censoring (JPC) scheme an effective approach to reducing costs. In this paper, we consider estimates of parameters with JPC data. Two populations, whose scale are same but shape which different, chosen be studied. We first evaluate maximum likelihood method. Because cannot obtained closed form, apply Newton–Raphson method part. Bayesian and corresponding credible intervals under squared error loss function computed by using Markov Chain Monte Carlo After that, use bootstrap calculate associated confidence unknown parameters. A simulation has been performed test feasibility above methods real data analysis also provided for illustrative purposes.