Bayesian Estimation of Birnbaum–Saunders Log-Linear Model

The Birnbaum–Saunders (BS) distribution was derived to model failure times of materials subjected to fluctuating stresses and strains. Motivated by applications in the characterizations of materials, in 1991 Rieck and Nedelman proposed a log-linear model for the BS distribution. This model has many applications, for instance, to compare the median time life of several populations or to assess the effect of covariates on accelerated life testing. In addition to the model studied under the classical approach, we considered Markov chain Monte Carlo (MCMC) and we made an implementation in WinBUGS to get a Bayesian approach under noninformative priori distribution. Similar results for both classical and Bayesian approaches were obtained. This implementation was also adapted for censoring and we assessed the influence of different percentages of censored data.