Empirical bayes estimators for the burr type XII accelerated life testing model based on type-2 censored data

The time to failure of an item is observed under a high stress, and the estimates are needed for the normal stress levels. This paper is concerned with empirical Bayes estimation of one of the two shape parameters (k) and the reliability function R(i) of the Burr type XII failure model based on type-2 censored data obtained from an accelerated life test. It is assumed that the effect of acceleration is to scale up the hazard rate, and that the parameter k has the natural conjugate prior with a known mean and unknown variance. Computations show good performance of the empirical Bayes estimators as compared with the corresponding maximum likelihood estimators.