Estimating Models of Program Management

Abstract

This research effort models decision-making behavior in a dynamic, uncertain environment. We derive consistent estimating procedures that model observed data that results from the decisions. This is accomplished by mating a Bayesian econometric process with a dynamic programming model of contractor behavior. This is used to demonstrate the dramatic increases in precision that can be obtained with just a few observations on program cost. The result of this effort can be used to develop a procedure for using routine data to help manage large programs in much the same way that control charts are routinely used to management production processes today.

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Document Details

Document Type
Technical Report
Publication Date
Dec 15, 2003
Accession Number
ADA419315

Entities

People

  • Jeff Camm
  • Norman K. Womer

Organizations

  • University of Mississippi

Tags

Communities of Interest

  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Basic Programming Language
  • Bayesian Networks
  • Computer Programming
  • Computer Programs
  • Contractors
  • Contracts
  • Learning
  • Load Monitoring
  • Observation
  • Optimization
  • Probability
  • Probability Distributions
  • Production
  • Production Rate
  • Program Management
  • Random Variables
  • Spreadsheet Software

Readers

  • Regression Analysis.
  • Software Engineering
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference