E-Bayesian Estimations and Its E-MSE For Compound Rayleigh Progressive Type-II Censored Data

Keywords: E-Bayesian estimation, Compound Rayleigh distribution, Progressive Type-II censored data, Survival functions, General Entropy loss function, Monte Carlo simulation

Abstract

Over the past decades, various methods to estimate the unknown parameter, the survival function, and the hazard rate of a statistical distribution have been proposed from the availability of type-II censored data. They are all differing in terms of how the progressive type-II censored data of the underlying distribution are available. In this study, we estimate the parameter, the survival function, and the hazard rate of the compound Rayleigh distribution by using the E-Bayesian estimation when the progressive type-II censored data are available. The resulting estimators are evaluated based on the asymmetric general entropy and the symmetric squared error loss functions. In addition, the E-Bayesian estimators under the different loss functions have been compared through a real data analysis and Monte Carlo simulation studies by calculating the E-MSE of the resulting estimators.

Author Biographies

Hassan Piriaei, Department of Mathematics, Borujerd Branch, Islamic Azad University, Borujerd, Iran
Assistant Professor of Statistics
Manoochehr Babanezhad, Department of Statistics, Faculty of Science, Golestan University, Gorgan, Golestan, Iran
Associate Professor of Statistics

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Published
2022-04-11
How to Cite
shojaee, O., Piriaei, H., & Babanezhad, M. (2022). E-Bayesian Estimations and Its E-MSE For Compound Rayleigh Progressive Type-II Censored Data. Statistics, Optimization & Information Computing, 10(4), 1056-1071. https://doi.org/10.19139/soic-2310-5070-1359
Section
Research Articles