Statistical inference for x-gamma distribution under progressive type II censoring

In this article, estimation problems for the x-gamma distribution with progressive type-II censoring are studied. The classical and Bayesian estimations for the model parameter are obtained by using maximum likelihood method, maximum product spacing and Markov chain Monte Carlo technique,respectively. Further, we explore the asymptotic confidence intervals, bootstrap confidence intervals and highest posterior density intervals for the model parameter. A simulation study is conducted to investigate the performance of the proposed point and interval estimations. Finally, a real data set is analyzed for illustration.