The estimation of the Burr-XII parameters with middle-censored data

Middle-censoring is considered as a modern general scheme of censoring. In this paper, we study the analysis of middle-censored data with Burr-XII distribution which is considered one of the most popular and flexible distributions for modeling stochastic events and lifetime for many products. The parameters are estimated by the maximum likelihood method and the Bayes estimation under gamma prior and by applying the Lindley's approximation. A simulation study is carried out to compare the performances of the two estimates. Both estimators behave almost similarly and verified the consistency property. A real medical data set is considered for illustration.