Inference for the Generalized Rayleigh Distribution Based on Progressively Type-II Hybrid Censored Data

Abstract

This paper considers the parameter estimation problem of test units following generalized Rayleigh distribution under progressive Type-II hybrid censoring scheme. The progressive Type-II hybrid censoring is a mixture of progressive Type-II and hybrid censoring schemes, which is provided to reduce the test cost. The Maximum Likelihood Estimators (MLEs) of the scale and shape parameters are derived using EM algorithm. Bayesian estimates of the unknown parameters are obtained under suitable priors by using the important sampling. Monte Carlo simulations are then performed for comparing the proposed methods.One real data set has been analyzed for illustrative purposes.