Reliability Estimation in Inverse Rayleigh Distribution Using Precautionary Loss Function

For estimating an unknown parameter and reliability function for the Inverse Rayleigh distribution, we obtained some Bayes estimators under Precautionary loss function using Non-informative prior, represented by Jefferys prior and Informative priors as Gamma prior. According to Monte-Carlo simulation study, the performance of these estimates is compared depending on the mean squared errors (MSE's), while the performance of reliability estimates is compared depending on the Integrated mean squared errors (IMSE's). In this paper we observe that, the performance of Bayes estimator under Precautionary loss function with Gamma prior is the best in performance than other estimators for all cases