Inferences for Weibull-Exponential Distribution Based on Progressive Type-II Censoring Under Step-Stress Partially Accelerated Life Test Model

AbstractThe object of this paper is to obtain point and interval estimations for the parameters of the Weibull-exponential distribution (WED) based on step-stress partially accelerated life tests model with progressive type-II censoring (PRO-II-C). Maximum likelihood (ML) and Bayes estimation method are used to estimate the unknown parameters of WED and the acceleration factor. Moreover, the approximate confidence intervals and asymptotic variance–covariance matrix have been acquired. Markov Chain Monte Carlo (MCMC) technique is applied to estimate the unknown parameters of WED and the acceleration factor. The Metropolis–Hastings algorithm is a MCMC method which used to generate samples from the posterior density functions. An example is applied for different estimation methods. Finally, a Monte Carlo simulation study is carried out to investigate the precision of Bayes estimates with MLEs and to compare the performance of different corresponding CIs.