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*
|
Companies:
|
|
Keywords:
|
Bayesian;
Experimental Design;
Defense;
Logistic Regression
|
Abstract:
|
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.
Back to the full JSM 2019 program
|