Table of Contents
Journal of Quality and Reliability Engineering
Volume 2013, Article ID 896807, 6 pages
Research Article

Bayesian Estimation Based on Rayleigh Progressive Type II Censored Data with Binomial Removals

1Department of Statistics, Parsabad Moghan Branch, Islamic Azad University, Parsabad Moghan, Iran
2Faculty of Science, Golestan University, Gorgan, Golestan, Iran

Received 4 October 2012; Revised 27 January 2013; Accepted 3 February 2013

Academic Editor: Mohammad Modarres

Copyright © 2013 Reza Azimi and Farhad Yaghmaei. 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.


This study considers the estimation problem for the parameter and reliability function of Rayleigh distribution under progressive type II censoring with random removals, where the number of units removed at each failure time has a binomial distribution. We use the maximum likelihood and Bayesian procedures to obtain the estimators of parameter and reliability function of Rayleigh distribution. We also construct the confidence intervals for the parameter of Rayleigh distribution. Monte Carlo simulation method is used to generate a progressive type II censored data with binomial removals from Rayleigh distribution, and then these data are used to compute the point and interval estimations of the parameter and compare both the methods used with different random schemes.