The use of Bayesian statistics and experimental design as tools to scope testing and analyze data related to defense has increased in recent years. Planning a test using experimental design will allow testers to cover the operational space while maximizing the information obtained from each run. Understanding which factors can affect a detector’s performance can influence military tactics, techniques and procedures, and improve a commander’s situational awareness when making decisions in an operational environment. This presentation will explain how a D-optimal experimental design could be an option for planning a test when the number of runs is limited but an adequate test is desired. Additionally, it will describe how the results of a Bayesian multiple logistic model could be used to show in what way the operational environment can affect the detector’s performance.
Suggested Citation
Anderson, Breeana G, Heather M Wojton, and Keyla Pagan-Rivera. D-Optimal as an Alternative to Full Factorial Designs: A Case Study. IDA Document NS D-10580. Alexandria, VA: Institute for Defense Analyses, 2019.