Bayesian estimation for topp-leone distribution using progressively censored data and asymmetric loss functions

In this study, based on progressive type-II censored data, Bayes estimators of the unknown parameter Topp-Leone distribution are derived by using informative and non-informative, priors under square error (symmetric), linex, general entropy, precautionary (asymmetric) loss functions. The cannot be obtained in closed-forms, for reason, Lindley’s approximation method is used to compute approximate estimates. asymptotic confidence highest posterior density credible intervals obtained. performances proposed compared with corresponding maximum likelihood estimator different sample sizes terms average estimate mean squared through an extensive simulation study. Finally, a real data set provided illustrate results.