Bayes Estimation and Expected Termination Time for the Competing Risks Model from Gompertz Distribution under Progressively Hybrid Censoring with Binomial Removals

This paper considers the Bayes estimation for competing risks model under Type-I progressively hybrid censoring with binomial removals from two-parameter Gompertz distribution. Bayes procedure is used to derive the estimations of the unknown parameters, reliability and hazard rate functions based on symmetric and asymmetric loss functions. The effect of varying removal probability p on the expected termination time point under Type-I PHC with binomial removals over the expected termination time point for the complete sample (REET) is investigated. Numerical experiments using Monte Carlo simulation are given to compare the performance of the proposed estimates. Finally, one data set was used for illustrative purposes in conclusion.