Bayesian and Non Bayesian Estimation of Erlang Distribution under Progressive Censoring
نویسنده
چکیده
Based on progressively Type-II censored samples, the maximum likelihood and Bayes estimators for the scale parameter, reliability and cumulative hazard functions are derived. The Bayes estimators are studied under symmetric (squared error) loss function and asymmetric (LINEX and general entropy) loss functions. Tow techniques are used for computing the Bayes estimates; standard Bayes and importance sampling methods. The performance of the estimates are compared by using the mean square error and the relative absolute bias through Monte Carlo simulation study.
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