Bayesian Inference for the Entropy of the Rayleigh Model Based on Ordered Ranked Set Sampling

Recently, ranked set samples schemes have become quite popular in reliability analysis and life-testing problems. Based on ordered ranked set sample, the Bayesian estimators and credible intervals for the entropy of the Rayleigh model are studied and compared with the corresponding estimators based on simple random sampling. These Bayes estimators for entropy are developed and computed with various loss functions, such as square error, linear-exponential, Al-Bayyati, and general entropy loss functions. A comparison study for various estimates of entropy based on mean squared error is done. A real-life data set and simulation are applied to illustrate our procedures.