Expected Bayesian estimation for exponential model based on simple step stress with Type-I hybrid censored data-Reference-Cited by-同舟云学术

Expected Bayesian estimation for exponential model based on simple step stress with Type-I hybrid censored data

Published:2022 Issue:10 Volume:19 Page:9773-9791
ISSN:1551-0018
Container-title:Mathematical Biosciences and Engineering
language:
Short-container-title:MBE

Author:

Nagy M.¹,Abu-Moussa M. H.²,Alrasheedi Adel Fahad¹,Rabie A.³

Affiliation:

1. Department of Statistics and Operation Research, Faculty of Science, King Saud University

2. Department of Mathematics, Faculty of Science, Cairo University, Giza-Egypt

3. Department of Mathematics, Faculty of Science, Al-Azhar University, Assiut, Egypt

Abstract

<abstract><p>The procedure of selecting the values of hyper-parameters for prior distributions in Bayesian estimate has produced many problems and has drawn the attention of many authors, therefore the expected Bayesian (E-Bayesian) estimation method to overcome these problems. These approaches are used based on the step-stress acceleration model under the Exponential Type-I hybrid censored data in this study. The values of the distribution parameters are derived. To compare the E-Bayesian estimates to the other estimates, a comparative study was conducted using the simulation research. Four different loss functions are used to generate the Bayesian and E-Bayesian estimators. In addition, three alternative hyper-parameter distributions were used in E-Bayesian estimation. Finally, a real-world data example is examined for demonstration and comparative purposes.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine

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