Bayes estimators with extension of Jeffery prior information for Time censored data and Failure censored data

Abstract

In this research, the Bayes estimator was derived based on Time censored data of the first type, and the Failure censored data of the second type. Reliance has been made on extension of Jeffery prior information. Finally, the simulation was used based on the MATLAB program and with different inputs to find the best estimator among Maximum Likelihood estimator and Bayes estimators with extension that has the least mean percentage error