E-Bayesian Estimation of Chen Distribution Based on Type-I Censoring Scheme

• Main Authors: Ali Algarni, Abdullah M. Almarashi, Hassan Okasha, Hon Keung Tony Ng
• Format: Article
• Language: English
• Published: MDPI AG 2020-06-01
• Series: Entropy
• Subjects: E-Bayes estimation; Bayes estimation; Chen distribution; type-I censoring scheme; balanced loss function
• Online Access: https://www.mdpi.com/1099-4300/22/6/636

In this paper, E-Bayesian estimation of the scale parameter, reliability and hazard rate functions of Chen distribution are considered when a sample is obtained from a type-I censoring scheme. The E-Bayesian estimators are obtained based on the balanced squared error loss function and using the gamma distribution as a conjugate prior for the unknown scale parameter. Also, the E-Bayesian estimators are derived using three different distributions for the hyper-parameters. Some properties of E-Bayesian estimators based on balanced squared error loss function are discussed. A simulation study is performed to compare the efficiencies of different estimators in terms of minimum mean squared errors. Finally, a real data set is analyzed to illustrate the applicability of the proposed estimators.