Statistical Inference for Gompertz Distribution based on Progressive Type-II Censored Data with Binomial Removals

• Main Authors: Manoj Chacko, Rakhi Mohan
• Format: Article
• Language: English
• Published: University of Bologna 2018-12-01
• Series: Statistica
• Subjects: Gompertz distribution; Progressive type-II censoring; Binomial removals; Bayes estimates; MCMC method
• Online Access: https://rivista-statistica.unibo.it/article/view/7847

In this paper, the problem of estimation of parameters for a two-parameterGompertz distribution is considered based on a progressively type-II censored sample with binomial removals. Together with the unknown parameters, the removal probability is also estimated. The maximum likelihood estimators of the parameters and the asymptotic variance-covariance matrix of the estimates are obtained. Bayes estimators are also obtained using different loss functions such as squared error, LINEX and general entropy. A simulation study is performed for comparison between various estimators developed in this paper. A real data set is also used for illustration.