Maximum Likelihood Estimation for the Three-parameter Log-gamma Distribution Under Type-II Censoring

In this paper, we study the maximum likelihood estimation of three parameters of the log-gamma distribution under Type-II censored samples. The score function of the shape parameter and the observed Fisher information are presented. The expected Fisher information matrix is derived through which the asymptotic variances and covariances of the MLEs are tabulated for various proportions of censoring. Finally, a life-test data in [27], and also analysed in [25], [26], and a simulated data set are used to illustrate the method of estimation developed in this paper.