Bayesian estimation of the parameters for two-parameter bathtub-shaped lifetime distribution based on ranked set sampling



Bayesian inference of the parameters for bathtub-shaped lifetime distribution based on simple random sampling (SRS) and ranked set sampling (RSS) are obtained. The Monte Carlo Markov chain is used, especially MetropolisHastings and Gibbs sampling. To compare different estimates, the Monte Carlo simulations are used. The results of simulation show that the estimators based on RSS are more efficient than based on SRS. Also, the length of highest posterior density (HPD) credible interval based on RSS is shorter than its SRS counterparts. Finally, a real data set has been analyzed for illustrative purposes.