Lindley procedure and MCMC technique in Bayesian estimation for Kumaraswamy Weibull distribution

In this study, a comparison between three methods for estimating unknown parameters of the Kumaraswamy Weibull distribution different sample sizes type II censoring data is presented. Specifically, we compare behaviors maximum likelihood estimates, Lindley and Markov chain Monte Carlo (MCMC) estimates as Bayesian estimates. We have not found any work on topic after reviews literature except one with little information about inference important distribution. The simplest form approximation posterior mean proposed approximate closed forms acceptable Bayes models multi-parameters such derived. A simulation conducted to investigate performances estimators. Finally, real examples are analyzed illustrate application possibility estimation methods. results reveal that, although, good performance estimators, estimators resulting in MCMC technique better sense squared errors.