Parametric Inference for Inverted Exponentiated Rayleigh Distribution under General Progressive Type II Censoring Scheme

A parametric inference of point and interval estimates for inverted exponentiated Rayleigh distribution with general progressive Type-II censoring scheme is studied using both classical and Bayesian estimation. The maximum likelihood method is used for estimating the unknown two-parameter inverted exponentiated Rayleigh distribution and some lifetime parameters such as survival and hazard rate functions in presence of general progressive Type-II censoring sampling. The approximate confidence intervals through Fisher information matrix, highest posterior density credible intervals for the two-parameter inverted exponentiated Rayleigh distribution, and any function of them, are constructed. In addition, Bayesian estimates of the unknown parameters are computed using two different loss functions squared error loss and linear exponential loss functions. A Markov Chain Monte Carlo method technique is applied to carry out Bayesian estimation procedure. Finally, a numerical simulation is carried out to assess the performance of the proposed methods and real data is analyzed using the suggested inference methods.