A Comparison between Some Bayesian Estimation Methods for Parameter Exponential Distribution by Using Data Type II Censoring

Abstract Due to the importance of exponential distribution, especially in the modeling and analysis of various data in several fields in mathematics and statistics, including the applied field (experiments) and the pure field (theories). Some tests do not provide sufficient information on the trial data, so they are called “censored data”. The aim of this paper is to compare some Bayesian estimation methods for the exponential distribution of parameters using data type II censoring. We provided an estimate of the scale parameter (ESP) for the exponential distribution under data the control of type II by using the proposed Bayesian method and maximum probability. We also compared these methods using Mean square error (MSE). This study was conducted using simulation with different parameter values (θ) and different sample sizes (n = 10, 20, 50, 100). The calculation results showed that the best method of estimation is the proposed Bayesian method (BAY2), which uses the distribution of Chi-Square (n) in the previous information.