Bayesian analysis of restricted random censorship model with burr type XII distribution

The article provides the bayesian analysis of restricted random censorship model with burr type xii distribution. it is seen that the joint continuous conjugate prior of the proposed model parameters cannot be derived; we consider in this paper the commonly used gamma prior distributions of these parameters. it is further seen that the explicit expressions of bayes estimates are not possible; we suggest two different methods of bayesian computation,namely,lindley’s method and markov chain gibbs sampling. the classical method of maximum likelihood estimation is considered for comparison purposes. numerical experiments are performed to check the properties of maximum likelihood estimators and bayes estimators. a real life data example is analyzed to illustrate the proposed methodology. the proposed model is validated using posterior predictive simulation in order to ascertain its appropriateness. © 2017 pakistan journal of statistics.