Regression Models of Quarterly Overhead Costs for Six Government Aerospace Contractors.

Abstract

Since overhead costs constitute a large percentage of total cost for aerospace contractors, it is important to be able to predict them accurately. The research performed in this thesis takes six government aerospace contractors and obtains regression models of their overhead costs that can be utilized for forecasting purposes. This method is preferable to some of the more commonly used methods because it estimates overhead costs directly, eliminating reliance upon predicted overhead rates. After the data were transformed to eliminate the effects of autocorrelation, excellent structural results were obtained for five of the six aerospace contractors. A Monte Carlo simulation was performed to compare various estimators of the autocorrelation. Two of the estimators were found to be superior. These two estimators are both two-stage estimators that are calculated utilizing Wallis's test statistic for fourth-order autocorrelation. (Author)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1986
Accession Number
ADA169185

Entities

People

  • David J. Jerabek

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Coefficients
  • Contractors
  • Data Science
  • Estimators
  • Governments
  • Information Science
  • Monte Carlo Method
  • Operations Research
  • Random Variables
  • Schools
  • Simulations
  • Statistical Algorithms
  • Statistics
  • Structural Analysis
  • United States
  • United States Naval Academy

Readers

  • Life Cycle Cost Analysis
  • Statistical inference.
  • Systems Analysis and Design

Technology Areas

  • Space