Birnbaum-Saunders Distribution for Software Reliability Data Analysis Using Markov Chain Monte Carlo Method

摘要

This paper demonstrates the analysis of Markov Chain Monte Carlo (MCMC) method to estimate the parameters of Birnbaum-Saunders (BS) model based on a complete sample. An established software for Bayesian analyses which uses Gibbs sampler technique (Open BUGS) is employed to obtain Bayes estimates for BS model which, assumes that the estimation of the parameters for the independent informative set of priors are sampled from the posterior density function. Moreover, computational ease for calculating the estimates and constructing the probability intervals has also been illustrated through the analysis of a real software reliability data.