Optimality of Bayesian Estimators: A Comparative Study Based on Exponential Progressive Type II Censored Data
Posted: 9 Nov 2018
Date Written: July 1, 2018
The paper investigates estimation problem of the parameter of exponential distribution. The maximum likelihood (ML) estimator and Bayesian estimators are obtained based on eight sampling schemes, six families of prior distributions, and seven classes of loss functions. The estimators are compared based on absolute relative error, standard deviation, mean square error, relative error, loss, risk, and Pitman closeness. The main objective is to select the loss function that yields an optimal estimator and optimal sampling scheme within a given class of estimators.
Keywords: Censoring Schemes, Bayes Estimators, Loss Functions, Pitman Closeness, Exponential Distribution
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