Bayesian Inference for the Parameter and Reliability Function of Basic Gompertz Distribution under Precautionary loss Function

Abstract

In this paper, some estimators for the unknown shape parameter and reliability function ofBasic Gompertz distribution have been obtained, such as Maximum likelihood estimator andBayesian estimators under Precautionary loss function using Gamma prior and Jefferys prior.Monte-Carlo simulation is conducted to compare mean squared errors (MSE) for all theseestimators for the shape parameter and integrated mean squared error (IMSE's) for comparingthe performance of the Reliability estimators. Finally, the discussion is provided to illustratethe results that summarized in tables.