two parameter exponential distribution

The use of the two-parameter exponential distribution model in fitting survival and reliability analysis data in the presence of censored random data has recently attracted the attention of a large number of authors. Considering the importance of the model, its parameter estimation is discussed using the method of moment, maximum likelihood and shrinkage estimation. To present the interval shrinkage estimator, it is first proved that the moment estimators are asymptotically unbiased and the interval shrinkage estimator performs better compared to other estimators. Finally, using two real data sets and statistical criteria, the goodness of fit of the model is compared with censored random data based on parameter estimation methods.

Our main objective in this paper is to analyze Bayesian Shrinkage Estimators of the parameter of two-parameter Exponential Distribution Scale under General Entropy Loss Function based on the prior conjugate distribution and Progressive Type-II Censored Data in the presence of the location parameter. To this end, in the present paper, firstly, we present Shrinkage Estimator of scale parameter based on the Bayesian estimator that obtained under General Entropy Loss Function, and prior conjugate distribution, and then investigate the efficiency of the proposed estimator with other estimators, such as maximum likelihood estimator, Bayes estimator, empirical Bayesian estimator, and empirical Bayesian Shrinkage Estimator. The method used in this paper to compute empirical Bayesian estimator, and empirical Bayesian Shrinkage Estimator is guessing. Using simulated data based on Monte Carlos’ method, under six censorship schemes and with two prior distributions of Jeffrey and Hartigan, the effectiveness of estimators is compared. Finally, using actual data, the efficiency of the proposed estimators will be examined.