Bayes approach for the series system with type-2 censoring

This work is focusing on a series system with n statistically independent components, each of which has a Pareto distributed lifetime with parameters tau_j and tita_j, j=1,2,3,…,n and which are censored when the r-th sample fails. Many products have more than one cause of failure. In masked system life time data, the causes of exact failure are often unknown. These observations are referred as masked. It is assumed that the lifetime data of the series system are masked, and the masking probability is dependent. A Bayesian analysis via gibbs sampling is made for estimating the unknown parameters using likelihood function. The results obtained are validated by a numerical example.