Table of Contents
Advances in Statistics
Volume 2014, Article ID 198696, 13 pages
http://dx.doi.org/10.1155/2014/198696
Research Article

Designing Bayesian Sampling Plans with Adaptive Progressive Hybrid Censored Samples

Wayne State University, Detroit, MI 48202, USA

Received 2 May 2014; Accepted 29 September 2014; Published 16 November 2014

Academic Editor: Chin-Shang Li

Copyright © 2014 TaChen Liang. 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.

Abstract

This paper studies the acceptance sampling for exponential distributions with type-I and type-II adaptive progressive hybrid censored samples. Algorithms are proposed for deriving Bayesian sampling plans. We compare the performance of the proposed sampling plans with the sampling plans of Lin and Huang (2012). The numerical results indicate that the proposed sampling plans outperform the sampling plans of Lin and Huang (2012).