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Activity Number: 340 - SPEED: Bayesian Methods, Part 1
Type: Contributed
Date/Time: Tuesday, July 30, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Defense and National Security
Abstract #306475
Title: The Use of Experimental Design and Bayesian Logistic Models in Defense Analysis: a Case Study
Author(s): Keyla Pagan-Rivera*
Keywords: Bayesian; Experimental Design; Defense; Logistic Regression

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 talk 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.

Authors who are presenting talks have a * after their name.

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