Modified censored moment estimation for the two-parameter Birnbaum-Saunders distribution
The maximum likelihood estimators (MLEs) and the moment estimators of a two-parameter Birnbaum-Saunders (BISA) distribution are studied by various authors when data are either complete or subject to Type-I or Type-H censoring. But there is not much research on parameter estimation for the BISA distribution under random censoring. A simple method of modified censored moment estimation is proposed to estimate parameters of the BISA distribution under random censoring. Bias-reduced versions of these estimators are constructed as well. Asymptotic theory for the estimators is established. The performance of these estimators is compared with that of the MLEs through Monte Carlo simulations for small, moderate, and large proportions of censoring and different sample sizes. An analysis of real data is used to illustrate the proposed method. (c) 2004 Elsevier B.V. All rights reserved.
modified censored moment estimator birnbaum-saunders distribution random censoring monte carlo simulations bias-reduced estimator probability coverage synthetic data