Bayes estimation for the parameters of the Weibull-Geometric distribution based on progressive first failure censored data
Abstract
In this paper, we deal with the problem of estimating the parameters of the Weibull-Geometric distribution based on progressive first-failure censoring scheme. The maximum likelihood and Bayes methods of estimation are used for this purpose. The Monte Carlo Integration (MCI) technique is used for computing the Bayes estimates. The Bayes estimates of the parameters are compared with their corresponding maximum likelihood estimates via Monte Carlo simulation study.
Copyright © 2016 Z.F. Jaheen, Sara M.A.M. Ali. 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
Z. F. Jaheen, S. M. A. M. Ali, Bayes estimation for the parameters of the Weibull-Geometric distribution based on progressive first failure censored data, J. Math. Comput. Sci. 6 (2016), 814–825.
BibTeX
@article{Jaheen2016,
author = {Jaheen, Z.F. and Ali, Sara M.A.M.},
title = {Bayes estimation for the parameters of the Weibull-Geometric distribution based on progressive first failure censored data},
journal = {J. Math. Comput. Sci.},
volume = {6},
year = {2016},
pages = {814--825},
doi = {}
}