Table of Contents
International Journal of Quality, Statistics, and Reliability
Volume 2009 (2009), Article ID 754896, 10 pages
http://dx.doi.org/10.1155/2009/754896
Research Article

A Demonstration of Modern Bayesian Methods for Assessing System Reliability with Multilevel Data and for Allocating Resources

Statistical Science, Los Alamos National Laboratory, Los Alamos, NM 87545, USA

Received 4 May 2009; Accepted 8 November 2009

Academic Editor: Shuen-lin Jeng

Copyright © 2009 Todd L. Graves and Michael S. Hamada. 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

Good estimates of the reliability of a system make use of test data and expert knowledge at all available levels. Furthermore, by integrating all these information sources, one can determine how best to allocate scarce testing resources to reduce uncertainty. Both of these goals are facilitated by modern Bayesian computational methods. We demonstrate these tools using examples that were previously solvable only through the use of ingenious approximations, and employ genetic algorithms to guide resource allocation.