Bayesian estimation for a multi step-stress accelerated generalized exponential model with type-II censored data
Abstract
We consider multiple step-stress accelerated life tests (SS-ALTs) assuming that the lifetime follows a generalized exponential distribution. Based on Type-II censored data, we calculate the maximum likelihood and Baysian estimates using MCMC. A Monte Carlo simulation study is carried out to examine the performance of the maximum likelihood and Baysin estimators through their mean squared error.
Copyright © 2017 Ghada Hussien Abdelmonem, Z. F. Jaheen. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Cite this article
G. H. Abdelmonem, Z. F. Jaheen, Bayesian estimation for a multi step-stress accelerated generalized exponential model with type-II censored data, J. Math. Comput. Sci. 7 (2017), 292–306.
BibTeX
@article{Abdelmonem2017,
author = {Abdelmonem, Ghada Hussien and Jaheen, Z. F.},
title = {Bayesian estimation for a multi step-stress accelerated generalized exponential model with type-II censored data},
journal = {J. Math. Comput. Sci.},
volume = {7},
year = {2017},
pages = {292--306},
doi = {}
}