Estimation on Lindely Weibull Distribution based on Progressive First Failure Censored Data

In this paper, we discuss the problem of estimating the parameters of the Lindely Weibull distribution based on progressive first-failure censoring scheme. The maximum likelihood and Bayes methods of estimation are used for this purpose. Markov chain Monte Carlo (MCMC) method is used to measure estimates of Bayes using Gibbs sampling procedure and the corresponding credible intervals are also to be constructed. To illustrate the proposed methods, we provide a numerical example. Finally, the Bayes estimates of the parameters are compared with their corresponding maximum likelihood estimates via Monte Carlo simulation study