Author

Yuqing Xiao

Date of Award

12-4-2006

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Mathematics and Statistics

First Advisor

Yu-Sheng Hsu - Chair

Second Advisor

Pulak Ghosh

Third Advisor

Tambra Dunams

Abstract

The U.S. Army¡¯s Chemical Demilitarization are designed to store, treat and destroy the nation¡¯s aging chemical weapons. It operates Near-Real-Time Monitors and Deport Area Monitoring Systems to detect chemical agent at concentrations before they become dangerous to workers, public health and the environment. CDC recommends that the sampling and analytical methods measure within 25% of the true concentration 95% of the time, and if this criterion is not met the alarm set point or reportable level should be adjusted. Two methods were provided by Army¡¯s Programmatic Laboratory and Monitoring Quality Assurance Plan to evaluate the monitoring systems based on CDC recommendations. This thesis addresses the potential problems associated with these two methods and proposes the Bayesian method in an effort to improve the assessment. Comparison of simulation results indicates that Bayesian method produces a relatively better estimate for verifying monitoring system performance as long as the prior given is correct.

Included in

Mathematics Commons

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