Bayesian Reliability- Combining Information

One of the most powerful features of Bayesian analyses is the ability to combine multiple sources of information in a principled way to perform inference. This feature can be particularly valuable in assessing the reliability of systems where testing is limited. At their most basic, Bayesian methods for reliability develop informative prior distributions using expert judgment or similar systems. Appropriate models allow the incorporation of many other sources of information, including historical data, information from similar systems, and computer models....

2016 · Alyson Wilson, Kassandra Fronczyk

Estimating System Reliability from Heterogeneous Data

This briefing provides an example of some of the nuanced issues in reliability estimation in operational testing. The statistical models are motivated by an example of the Paladin Integrated Management (PIM). We demonstrate how to use a Bayesian approach to reliability estimation that uses data from all phases of testing. Suggested Citation Browning, Caleb, Laura Freeman, Alyson Wilson, Kassandra Fronczyk, and Rebecca Dickinson. “Estimating System Reliability from Heterogeneous Data.” Presented at the Conference on Applied Statistics in Defense, George Mason University, October 2015....

2015 · Caleb Browning, Laura Freeman, Alyson Wilson, Kassandra Fronczyk, Rebecca Medlin

Statistical Models for Combining Information Stryker Reliability Case Study

Reliability is an essential element in assessing the operational suitability of Department of Defense weapon systems. Reliability takes a prominent role in both the design and analysis of operational tests. In the current era of reduced budgets and increased reliability requirements, it is challenging to verify reliability requirements in a single test. Furthermore, all available data should be considered in order to ensure evaluations provide the most appropriate analysis of the system’s reliability....

2015 · Rebecca Medlin, Laura Freeman, Bruce Simpson, Alyson Wilson

A Bayesian Approach to Evaluation of Land Warfare Systems

This presentation is a presentation for the Army Conference on Applied Statistics. The presentation covers a brief introduction to land warfare problems, and devises a methodology using Bayes Theorem to estimate parameters of interest. Two examples are given, a simple one using independent Bernoulli Trials, and a more complex one using correlated Red and Blue casualty data in a Loss Exchange Ratio and a hierarchical model. The presentation demonstrates that the Bayesian approach is successful in both examples at reducing the variance of the estimated parameters, potentially reducing the cost of devising a complex test program....

2012 · Alyson Wilson, Robert Holcomb, Lee Dewald, Samuel Parry