Estimating the Parameters of the Generalized Exponential Distribution in Presence of Hybrid Censoring

Abstract

The two most popular censoring schemes are Type-I and Type-II censoring schemes. Hybrid censoring scheme is a mixture of Type-I and Type-II censoring schemes. In this article, we mainly consider the analysis of hybrid censored data when the lifetime distribution of the individual item is a two-parameter generalized exponential distribution. It is observed that the maximum likelihood estimators cannot be obtained in closed form. We propose to use the EM algorithm to compute the maximum likelihood estimators. We obtain the observed Fisher information matrix using the missing information principle and it can be used for constructing the asymptomatic confidence intervals. We also obtain the Bayes estimates of the unknown parameters under the assumption of independent gamma priors using the importance sampling procedure. One data set has been analyzed for illustrative purposes.