Accession Number:

ADA056502

Title:

An Evaluation of a Bayesian Approach to Compute Estimates-at-Completion for Weapon System Programs.

Descriptive Note:

Master's thesis,

Corporate Author:

AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OHIO SCHOOL OF ENGINEERING

Personal Author(s):

• Hayes,Richard A.

Report Date:

1977-12-01

Pagination or Media Count:

93.0

Abstract:

The Bayesian model developed to predict costs-at-completion on weapon system programs is an extension of research done by M. Zaki El-Sabban. The model assumes cost is a random variable and is normally distributed. Budgeted costs are used to develop the prior probability distribution. Actual cost information is used for the Bayesian updating of the probability distribution. The mean of the updated probability distribution is the new estimated cost-at-completion for the program. The model was compared with a non-linear regression model and a linear extrapolation model on five weapon system programs. On three of the programs the non-linear regression model estimated the final cost the greater percentage of the time. On the remaining two programs the Bayesian model estimated the final cost the greater percentage of the time. The Bayesian model demonstrated several advantages over previous models use at the beginning of the program, inclusion of subjective information, and giving weight to future program budgets.

Descriptors:

• *COST ESTIMATES
• *COST MODELS
• *BAYES THEOREM
• *MILITARY PROCUREMENT
• MATHEMATICAL MODELS
• PROBABILITY DISTRIBUTION FUNCTIONS
• THESES
• REGRESSION ANALYSIS
• MATHEMATICAL PREDICTION
• MILITARY BUDGETS
• EXTRAPOLATION

Subject Categories:

• Administration and Management
• Economics and Cost Analysis
• Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE