OPTIMUM BAYESIAN INFERENCE FOR 3-STEP STEP-STRESS TESTS UNDER TYPE-II CENSORING

The optimum model for 3-step step-stress tests under Type-II censoring from a Bayesian setup is proposed. Numerical examples are presented to illustrate all the methods of inference developed here, and a comparison of the ML and Bayesian methods is also carried out. The criteria of minimum asymptotic variance of the maximum likelihood estimator of the mean life at a design stress are used to obtain the optimal test plan. Further, several numerical examples are presented to demonstrate the proposed methods, and sensitivity analyses of the optimal plans are also carried out.